14Oct

Sec Gen : Développeur fullstack confirmé H/F at Ministère de l’Économie et des Finances – France, Ile-de-France, Paris (75)



Informations générales


Référence

2024-19866  


Date de début de publication

14/10/2024


Date limite d’envoi des candidatures

30/11/2024


Documents requis pour postuler

CV
Lettre de motivation


Directions et Services

Service du numérique (SNUM)

Description du poste


Domaine et métier

Numérique – Développeuse / Développeur


Intitulé du poste

Sec Gen : Développeur fullstack confirmé H/F


Cotation RIFSEEP

Cotation 3


Versant

salaryrange”>Fonction publique de l’Etat


Catégorie

Catégorie A (cadre)


Statut du poste

Vacant


Nature de l’emploi

Emploi ouvert aux titulaires et/ou aux contractuels


Descriptif de l’employeur

Au sein du secrétariat général, le Service du Numérique (SNUM) est chargé d’animer la gouvernance ministérielle des systèmes d’information en lien avec les orientations interministérielles en la matière. A ce titre, il assure la coordination avec la direction interministérielle du numérique. Il coordonne la transformation numérique et le développement de l’usage du numérique sur le périmètre des ministères. Il conduit des actions de soutien à l’innovation numérique. Il exerce la fonction de délégué à la protection des données en lien avec la Commission nationale de l’informatique et des libertés ainsi que celle d’administrateur ministériel des données, chargé de faire émerger et d’accompagner les projets de valorisation de la donnée. Il assure pour l’administration centrale des MEF les fonctions de pilotage et de support recouvrant le développement et la maintenance de l’offre de service numérique. Il est structuré autour :

– d’une sous-direction opérationnelle sur le périmètre SI de l’administration centrale, disposant des compétences et des fonctions nécessaires à la conception et à la gestion opérationnelle du SI de l’administration centrale,

 – d’un bureau transverse chargé de l’aide à la gouvernance et fonctions supports.

– de 4 entités appelées “Missions” (dont le Bercy Hub initiateur de cette fiche) en charge de porter la stratégie interministérielle, la coordination ministérielle ou le pilotage de projets transverses au sein du ministère (MEFSIN).

 


Descriptif de l’employeur (suite)

 

Au sein du SNUM, l’entité en charge de la fonction « Administrateur ministériel des données – Bercy Hub » assure les fonctions suivantes :

– administrateur ministériel des données, des algorithmes et des codes sources : coordination des référents et des acteurs directionnels de la donnée, élaboration et coordination de la feuille de route ministérielle de la donnée, appui à la gouvernance et à la valorisation du patrimoine ministériel de la donnée ;

– Pilotage de l’incubateur du MEFSIN au bénéfice des directions (méthodes, outils et expertises)

– Innovation dans le domaine du numérique et des données, comme la connaissance et la valorisation des données.

Cette mission est donc en charge d’impulser et coordonner au sein du MEFSIN l’administration ministérielle des données dont les initiatives OpenData en coordination étroite avec la DINUM et les directions, d’animer et valoriser les échanges autour du numérique, d’encourager, soutenir et animer les initiatives d’entreprenariat, dans le cadre de startup d’Etat, et de l’innovation ouverte facilitant des produits numériques transformants.

Dans le cadre de son activité, la mission accompagne les équipes de Bercy à la réalisation des projets demandés par les différents services du ministère.


Description du poste

En tant que développeur fullstack au sein du Bercy Hub, vous interviendrez sur l’ensemble de projets traités par l’incubateur dans le but de réaliser une maquette (POC et MVP) et également le passage à l’échelle. Les projets pris en charge au sein de l’incubateur sont innovants, variés et ont pour but l’amélioration de l’efficience du service public. La méthode de gestion de projets est l’Agile – mode produit.

Responsabilités principales :

– Participer au cadrage des projets pilotés par le Bercy Hub.

– Être moteur dans la construction de la maquette permettant de confirmer l’adéquation de la solution proposée. Plusieurs niveaux de maquettage à réaliser : UX Figma et POC.

– Réalisation du MVP associé au projet, présentation et prise en compte de remarques client.

– Ecrire les spécifications fonctionnelles et identifier les cas de tests à mettre en place (test unitaires, tests fonctionnels et tests automatiques).

– Proposer / participer à la création de solution d’architecture logicielle répondant aux exigences exprimées.

– Coder la solution logicielle présentée dans le document d’architecture validé.

– Assurer la stabilisation et le niveau de qualité attendu par le client.

– Participer à la mise en exploitation de l’application ou du service créé.

 

 

Ce poste est un CDD de 12 mois.


Description du profil recherché

– Diplôme d’ingénieur ou universitaire en informatique avec une première expérience réussie (premier contrat ou projet perso démontrable).

-Maîtrise des technologies WEB : REST API (création et utilisation), serveurs Apache, NGINX, Flask. En plus des langages spécifique web (front et back), maîtriser Python, et au minimum un autre langage OO comme Java.

– Excellentes compétences en communication orale et écrite, avec la capacité de présenter des résultats complexes de manière claire et accessible.

– Forte capacité en travailler en équipe.

 


Temps Plein

Oui

Compétences candidat


Compétences

  • CONNAISSANCES – Bureautique et outils collaboratifs
  • CONNAISSANCES – Conduite et gestion de projet
  • CONNAISSANCES – Matériels, systèmes et réseaux d’information et de communication
  • SAVOIR-FAIRE – Maîtriser les délais
  • SAVOIR-FAIRE – Prendre en compte un contexte, une contrainte, une complexité
  • SAVOIR-ÊTRE – Aptitude à l’écoute
  • SAVOIR-ÊTRE – Avoir l’esprit d’équipe
  • SAVOIR-ETRE – Esprit d’initiative
  • SAVOIR-ÊTRE – Être rigoureux
  • SAVOIR-ÊTRE – Sens de l’innovation/Créativité
  • SAVOIR-ÊTRE – Sens de la pédagogie


Niveau d’études min. souhaité

Niveau 7 Master/diplômes équivalents


Niveau d’expérience min. requis

Confirmé

Informations complémentaires


Fondement juridique du recrutement

Art L332-2


Télétravail possible

Oui


Management

Non

Localisation du poste


Localisation du poste

France, Ile-de-France, Paris (75)


Lieu d’affectation


120 rue de Bercy – 75012 PARIS

Renseignements et contact – Note : les candidatures se font obligatoirement depuis l’application


Date de vacance de l’emploi

01/11/2024


Personne ou service à contacter pour obtenir plus d’informations sur l’offre



vl*********@fi******.fr













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14Oct

Senior Product Manager at AirAsia – Kuala Lumpur – RedQ


Job Description

Join our dynamic team at AirAsia as a Senior Product Manager and help shape the future of customer and merchant experiences across our digital platforms.

You’ll work at the intersection of technology and business, driving innovation and delivering impactful solutions that elevate the AirAsia brand. If you’re passionate about creating seamless, multi-channel digital experiences and thrive in fast-paced, collaborative environments, this role is made for you.

WHAT YOU’LL CHAMPION: ​

  • Work closely with stakeholders in AirAsia to conceptualize, define, design, develop and deliver the product backlog to provide a device, channel and medium independent experience to customers and merchant in the areas of customer support, merchant support, back office systems, etc
  • Bring ease of use and simplicity to AirAsia digital platforms enhancing the overall customer and merchant experience
  • Work with software engineering team to work on new ideas from conceptualization to prototyping to engineering to production
  • Providing vision and direction to the Agile development teams and stakeholders throughout the project and create requirements and stories
  • Ensure that the team always has an adequate amount of groomed backlogs to work on.
  • Plan and prioritize product feature backlog and development for the product
  • Define product vision, road-map and growth opportunities
  • Assess value, develop cases, and prioritize stories, epics and themes to ensure work focuses on those with the maximum value that is aligned with product strategy
  • Lead the planning of product release plans and set the expectation for delivery of new functionalities
  • Play an active role in mitigating impediments impacting successful team completion of Release/Sprint Goals Research and analyze market, the users, and the roadmap for the product
  • Follow our competitors and the industry
  • Keep abreast with Agile/Scrum best practices and new trends

WHO YOU ARE:

  • Hold a degree in Computer Science, Engineering or relevant field
  • Has overall 6+ years of experience with minimum 3 years in Product Management role, preferably in E-Commerce, Customer Support, Merchant Support Familiarity with A/B testing and conversion rate optimization (CRO)
  • Previously managed high traffic E-Commerce sites (500k+ visitors per day)
  • Good understanding of APIs and Microservices, Data Science, UI/UX, Javascript and/or python
  • Good understanding of cloud (preferably Google cloud) and associated areas like app engine, pub/sub, cloud storage, monitoring, big query etc In-depth knowledge of Agile processes and principles
  • Outstanding communication, presentation and leadership skills
  • Prior experience working in the Travel or Ecommerce domain is a big plus
  • Excellent organisational and time management skills Sharp analytical and problem-solving skills Creative thinker with a vision



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14Oct

Software Engineer (Python) at Garda Capital Partners – Wayzata, Minnesota, United States


Garda Capital Partners (Garda) is a multi-billion dollar alternative investment firm with over 20 years of experience deploying relative value strategies across fixed income markets for institutional investors. Garda has offices in Wayzata, New York City, West Palm Beach, Geneva, Zug, Copenhagen, Singapore, and Scottsdale.

Garda is looking to hire a Software Engineer to be a part of our Research and Technology (R&T) team based out of our Wayzata office. This is an exciting position offering opportunities to gain exposure to enterprise software development practices at a global hedge fund.

Position Responsibilities:

  • Aid in the development of new lines of business solutions using Python, Excel and Relational Databases
  • Support senior staff in designing and implementing complete solutions for our Risk and Front Office Groups.
  • Provide support for in-house and 3rd party applications

Qualifications & Desired Skills:

  • 3+ Year of object-oriented development, preferably with Python (using common programming design patterns and good practices)
  • 3+ Year of relational databases and SQL experience, data modeling, and database design
  • Experience with Python Data Science Stack (Pandas, NumPy, SQLAlchemy, etc.)
  • Experience with gRPC a plus
  • Experience with C# and JavaScript, React a plus
  • Bachelor’s or Master’s Degree in Computer Science, Engineering, Mathematics, or Finance
  • Strong analytical and problem-solving skills
  • Passionate about programming and technology
  • Interest in financial trading industry
  • Ability to work effectively in a high-energy, time sensitive team environment
  • Detail-oriented with strong verbal and written communication skills
  • Knowledge of fixed income trading and related financial instruments including bonds and interest rate derivative products preferred, but not required

This role is also eligible for other forms of compensation and benefits, such as a discretionary bonus, healthcare plan, 401(k) matching program, etc. Within the range, individual pay is determined by work location and additional factors, such as job-related skills, experience, and relevant education.

Base Salary for this role is expected to be between:$100,000—$150,000 USD



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13Oct

Data Engineer Consultant at Version 1 – Bengaluru, India


Company Description

Version 1 has celebrated over 26 years in Technology Services and continues to be trusted by global brands to deliver solutions that drive customer success. Our expertise enables our customers to navigate the rapidly changing Digital-First world we live in. We foster strong partnerships with leading technology giants including Microsoft, AWS, Oracle, Red Hat, OutSystems, and Snowflake, ensuring that our customers are provided with the highest quality solutions and services.

We’re an award-winning employer reflecting how our employees are at the very heart of Version 1 and what we do:

  • UK & Ireland’s premier AWS, Microsoft & Oracle partner
  • 3400+ strong, €350/£300m revenue business
  • 10+ years as a Great Place to Work in Ireland & UK
  • Best Workplace for Women in the UK & Ireland by GPTW
  • Best Workplace for Wellbeing in the UK by GPTW

We’re a core values driven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you!

Job Description

This is an exciting opportunity for an experienced developer of large scale digital & data solutions. You will join a team delivering a transformative cloud hosted application for a key Version 1 customer.

The ideal candidate will have a proven track record in implementing data ingestion and transformation pipelines for large scale organisations. We are seeking someone with deep technical skills in a variety of technologies to play an important role in developing and delivering early proofs of concept and production implementation.

You will ideally have experience in building solutions using a variety of tools & Microsoft Azure services, and a proven track record in delivering high quality work to tight deadlines.

Qualifications

Essential

  • 4 – 8 years of Hands on experience in designing and delivering data solutions using the Azure Data services including Azure Data Factory, Azure SQL Database, Azure Synapse, and Azure Data Lake.
  • Proficient in writing SQL, Stored procedures, and views. Creating and optimizing complex queries, analyzing query performance, using partitioning and clustering.
  • hands-on experience with enterprise BI platforms such as Power BI, Tableau, or Qlik Sense.
  • Experience building data solutions using ETL / ELT tools such as SQL Server Integration Services (SSIS), Oracle Data Integrator (ODI), and Talend.
  • Direct experience of building data pipelines using Azure Data Factory.
  • Comprehensive understanding of data management best practices including demonstrated experience with data profiling, sourcing, and cleansing routines utilizing typical data quality functions involving standardization, transformation, rationalization, linking and matching.
  • Advanced RDBMS experience including complex stored procedures, functions, query optimization, indexing strategy etc.
  • Experience in effectively coaching novice developers.
  • Good problem solving and data analysis skills.
  • Excellent written and oral communication skills, ability to communicate complex concepts.
  • Ability to translate business requirements into technical solutions.
  • Full project lifecycle experience, from initial concept through to deployment and support

Desirable:

  • Programming experience; in particular with Python.
  • Experience working with offshore team Consultancy experience.
  • Knowledge of Agile/Scrum is desirable.

Additional Information

Why Version 1?

At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their wellbeing, professional growth, and financial stability.

  • Share in our success with our Quarterly Performance-Related Profit Share Scheme, where employees collectively benefit from a share of our company’s profits.
  • Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme.
  • Flexible/remote working, Version 1 is tremendously understanding of life events and people’s individual circumstances and offer flexibility to help achieve a healthy work life balance.
  • Financial Wellbeing initiatives including; Pension, Private Healthcare Cover, Life Assurance, Financial advice and an Employee Discount scheme.
  • Employee Wellbeing schemes including Gym Discounts, Bike to Work, Fitness classes, Mindfulness Workshops, Employee Assistance Programme and much more. Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies.
  • Educational assistance, incentivised certifications, and accreditations, including AWS, Microsoft, Oracle, and Red Hat.
  • Reward schemes including Version 1’s Annual Excellence Awards & ‘Call-Out’ platform.
  • Environment, Social and Community First initiatives allow you to get involved in local fundraising and development opportunities as part of fostering our diversity, inclusion and belonging schemes.

And many more exciting benefits… drop us a note to find out more.

#LI-BS1



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13Oct

Data Driven | Data Engineer at Devoteam – Lisboa, Portugal


Company Description

At Devoteam, we believe that technology with strong human values can actively drive change for the better. Discover how Tech for People unlocks the future, creating a positive impact on the people and the world around us. We are a global leading player in Digital Transformation for leading organisations across EMEA, with a revenue of €1B. We believe in transforming technology to create value for our clients, partners and employees in a world where technology is developed for people. We are proud of the culture we have built together. We are proud of our people at the service of technology. We are proud of our diverse environment. Because we are #TechforPeople. Join our multidisciplinary team of Cloud experts, Designers, Business consultants, Security experts, Engineers, Developers and other extraordinary talents, spread across more than 20 EMEA countries. Become one of our +10.000 tech and business leaders on cloud, data and cyber security. Let’s fuse creativity with technology together and build innovative solutions that actively change things for the better.

Job Description

We are looking for a Data Engineer with experience in Python and ETL processes to deliver high quality data tools and support the business, with the following main responsibilities:

  • Develop and design data pipelines/ETL in Python.
  • Industrialize processes for full automation Assess client needs, understand the business and deliver a proper solution Build and design visualization tools (e.g dashboards).
  • Be the point of contact of the business for new suggestions and ways to enhance and improve the users BAU life (in data related topics).
  • Work closely with other Data Engineers to drive forward the DataHub and the data offer available to other teams within the bank.

Qualifications

  • Bachelor’s or Master’s degree in IT or equivalent.
  • At least 3 years of experience as a Data Engineer.
  • Technically proficient with Python development language and Python libraries (e.g.: PySpark, Spark, Numpy, Pandas…).
  • Experience with visualization tools such as Microsoft Power Bi.
  • Proficient with SQL.
  • Good communication skills.
  • Proficient Level of English (spoken and written).

Additional Information

The Devoteam Group works for equal opportunities, promoting its employees based on merit and actively fights against all forms of discrimination. We are convinced that diversity contributes to the creativity, dynamism and excellence of our organization. All of our vacancies are open to people with disabilities.



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13Oct

Country and Marketing Analytics Manager at Grab – Jakarta, Indonesia


Company Description

About Grab and Our Workplace

At Grab, every Grabber is guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles – the 4Hs: Heart, Hunger, Honour and Humility. These principles guide and help us make decisions as we create economic empowerment for the people of Southeast Asia.

Job Description

Get to know our Team

Grab – the leading super app in Southeast Asia – combines transport, food delivery, logistics, payments, and much more in a single platform. The Country & Marketing Analytics (CAMA) team helps us by being countries analytics consultant and strategic partner for partners such as operation & strategy, marketing, and growth function, deciphering the impact on our business, our brand and our users growth, to expand the outcome of future programs.

 

Get to know the Role

We are looking for a Country and Marketing Analytics Manager to lead data scientists (analytics) team which support Delivery (GrabFood, GrabMart), “Omnicommerce”, and Commercial (Partnership, Ads, and Brand Monetization) business, a person experienced in balancing people management,, and technical data science expertise. You have passion not only in growing, coaching, and inspiring the team but also bringing analytical frameworks to our team member to lead strategy and help bridge the gap between data science decisions. You’ll reporting to Marketing Analytics Manager II. The working arrangement for this role is hybrid.

 

The Critical Tasks You Will Perform

  • You will explore business, marketing, and growth opportunities, uncover insights, and identify areas for growth.
  • You will work with marketing growth and product marketing teams that influence main user growth decisions.
  • You will develop and test data-driven hypotheses to address main challenges.
  • You will partner up with the marketing and growth team in accomplishing, and evaluating projects and broaden Grab’s data capabilities for deeper insights.
  • You will develop analytics measurement frameworks, user segmentations, and channels attribution techniques to improve efficiency in solving problems.
  • You will support team members in their professional development. Inspiring and coaching them to grow as individuals and as team players.

Qualifications

What Essential Skills You Will Need

  • We are looking for someone with at least 6 years in Analytics, Business Intelligence, or Data Science role.
  • You have expertise in maintaining high measurement standards, designing and analysing experiments, using SQL/Python for data queries/analysis, and proficient in data visualisation tools like PowerBI.
  • You have experience with Big Data technologies such as Spark and PySpark. Experienced in handling large datasets and able to guide team members managing complex Extract, Transform and Load (ETL) processes.
  • You have a foundation in statistics and practical experience with controlled experiments in the industry.
  • You have experience influencing marketing or growth decisions based on quantitative analysis.
  • You can help, narrowing down multiple options into the best approach, and take ownership of open-ended ambiguous business problems. Propose novel solutions that go beyond common practice

Additional Information

Life at Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

  • We have your back with Term Life Insurance and comprehensive Medical Insurance.
  • With GrabFlex, create a benefits package that suits your needs and aspirations.
  • Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
  • We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life’s challenges.

What we stand for at Grab

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.



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13Oct

Staff Software Engineer at ServiceNow – San Diego, California, United States


Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

What you get to do in this role:

 

ServiceNow has been at the forefront of the AI revolution and continues to innovate thanks to its investment in fundamental research and infrastructure. Help us bring that innovation to our customers by collaborating with ServiceNow Research and platform engineering teams to introduce Agentic AI to the ecosystem. ServiceNow’s unique position at the heart of the world’s enterprise workflows provides an opportunity for engineers like you to build amazing features that put AI to work in ever more incredible ways.

As part of the PlatformX team, your job is to create innovative solutions for features that use AI agent frameworks, our LLMs, and the ServiceNow platform. You’ll face challenging work with a dynamic team of developers and introduce game-changing features that move ServiceNow into the next generation of enterprise grade solutions. 

PlatofrmX is a special team of motivated engineers and researchers that want to explore new technologies and find tangible solutions for challenging problems.  We’re looking for self-driven and experienced developers that love to work in uncharted territories and collaborate with teams across a large engineering organization to get their ideas into production.

What you get to do in this role:

  • Build, run, and test AI agents

  • Use benchmarking tools to evaluate performance

  • Work with LLM teams to improve model performance

  • Build applications on the platform to leverage AI capabilities

  • Collaborate with researchers and engineering teams

Qualifications

To be successful in this role you have:

  • 8+ years of software engineering experience
  • Familiarity with A.I. and LLMs   Experience in one or more of Search, Natural Language Processing, Knowledge Graphs, Conversational Agents, Personalization, and Causal Inference, Reinforcement Learning, etc.
  • Proficiency in Python, Java, and/or JavaScript

  • Knowledge of containerization and Kubernetes

Preferred experience but not required:

  • Knowledge of Golang, Rust, and/or C/C++ 

  • Familiarity with ServiceNow platform development 

 

FD21

For positions in California (outside of the Bay Area), we offer a base pay of $142,700 – $249,800, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs (subject to eligibility requirements). Compensation is based on the geographic location in which the role is located, and is subject to change based on work location. For individuals who will be working in the Bay Area, there is a pay enhancement for positions located in that geographical area; please contact your recruiter for additional information.

Not sure if you meet every qualification? We still encourage you to apply! We value inclusivity, welcoming candidates from diverse backgrounds, including non-traditional paths. Unique experiences enrich our team, and the willingness to dream big makes you an exceptional candidate!

Additional Information

Work Personas 

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work. Learn more here.

Equal Opportunity Employer 

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. 

Accommodations 

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact

ta****************@se********.com











 for assistance. 

Export Control Regulations 

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. 

From Fortune. ©2024 Fortune Media IP Limited. All rights reserved. Used under license. 



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12Oct

Senior Manager, Technology Enablement Advisory at Huron – New York – 1166 Ave of Americas


The Opportunity

Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future. 

Join our team as the expert you are now and create your future.

Position Summary

As an Advisor, Senior Manager of Technology Enablement, you will advise clients across diverse industries, including financial services, healthcare, and other sectors, on technology initiatives. Your responsibilities will include helping clients optimize their operations, drive digital transformation, comply with industry-specific regulations, and integrate emerging technologies. You will leverage industry knowledge and technical expertise to deliver customized solutions that enable regulatory adherence, innovation, and operational efficiency.

This role requires a background in consulting combined with extensive experience in implementing and managing software solutions across multiple technologies and industries.

Qualifications

Key responsibilities:

  • Industry-Specific Technology Enablement: Customize technology enablement strategies based on the unique challenges of diverse industries.
  • Regulatory & Risk Management: Support internal teams to advise clients on meeting industry-specific regulatory requirements.
  • Technology Integration: Ensure the seamless integration of new technologies with existing systems, whether it be financial platforms, healthcare systems, or other enterprise resource systems. Ensure that technology implementations improve business operations, customer experiences, and regulatory compliance.
  • Project Management & Delivery: Support the execution of technology projects across various industries. Ensure on-time, on-budget delivery of projects, managing cross-functional teams, including internal stakeholders, clients, and vendors.
  • Team Leadership & Mentorship: Lead and develop a high-performing consulting team including off-shore resources. Provide mentorship and foster a collaborative, results-driven culture. Guide teams in delivering tailored technology solutions for diverse clients.

Qualifications

  • 10+ years of experience in implementing and managing software applications across diverse industries.
  • A minimum of 5 years of consulting experience
  • Experience managing offshore teams
  • Strong knowledge of risk management controls development and testing.
  • Proven track record in creating technology solutions within a complex, regulated environments including Financial Institutions and Healthcare.
  • Effective communication skills, both written and verbal.
  • Analytical mindset with strong problem-solving abilities.
  • Proficiency in software and tools including machine learning and artificial intelligence.
  • Bachelor’s degree in Computer Science, or a related field

Technical Skills

  • Open AI ,Java, Python, JavaScript, C#/.NET, SQL, R or Scala
  • Cloud computing platforms (AWS, Azure, Google Coud Platform (GCP)) are a plus

The estimated base salary range for this job is $150,000 – $215,000. The range represents a good faith estimate of the range that Huron reasonably expects to pay for this job at the time of the job posting. The actual salary paid to an individual will vary based on multiple factors, including but not limited to specific skills or certifications, years of experience, market changes, and required travel. This job is also eligible to participate in Huron’s annual incentive compensation program, which reflects Huron’s pay for performance philosophy. Inclusive of annual incentive compensation opportunity, the total estimated compensation range for this job is $172,500 – $268,750. The job is also eligible to participate in Huron’s benefit plans which include medical, dental and vision coverage and other wellness programs. The salary range information provided is in accordance with applicable state and local laws regarding salary transparency that are currently in effect and may be implemented in the future.

Posting Category

Diversified

Opportunity Type

Regular

Country

United States of America



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12Oct

Gaussian Naive Bayes, Explained: A Visual Guide with Code Examples for Beginners | by Samy Baladram | Oct, 2024


CLASSIFICATION ALGORITHM

Bell-shaped assumptions for better predictions

⛳️ More CLASSIFICATION ALGORITHM, explained:
· Dummy Classifier
· K Nearest Neighbor Classifier
· Bernoulli Naive Bayes
Gaussian Naive Bayes
· Decision Tree Classifier
· Logistic Regression
· Support Vector Classifier
· Multilayer Perceptron (soon!)

Building on our previous article about Bernoulli Naive Bayes, which handles binary data, we now explore Gaussian Naive Bayes for continuous data. Unlike the binary approach, this algorithm assumes each feature follows a normal (Gaussian) distribution.

Here, we’ll see how Gaussian Naive Bayes handles continuous, bell-shaped data — ringing in accurate predictions — all without getting into the intricate math of Bayes’ Theorem.

All visuals: Author-created using Canva Pro. Optimized for mobile; may appear oversized on desktop.

Like other Naive Bayes variants, Gaussian Naive Bayes makes the “naive” assumption of feature independence. It assumes that the features are conditionally independent given the class label.

However, while Bernoulli Naive Bayes is suited for datasets with binary features, Gaussian Naive Bayes assumes that the features follow a continuous normal (Gaussian) distribution. Although this assumption may not always hold true in reality, it simplifies the calculations and often leads to surprisingly accurate results.

Bernoulli NB assumes binary data, Multinomial NB works with discrete counts, and Gaussian NB handles continuous data assuming a normal distribution.

Throughout this article, we’ll use this artificial golf dataset (made by author) as an example. This dataset predicts whether a person will play golf based on weather conditions.

Columns: ‘RainfallAmount’ (in mm), ‘Temperature’ (in Celcius), ‘Humidity’ (in %), ‘WindSpeed’ (in km/h) and ‘Play’ (Yes/No, target feature)
# IMPORTING DATASET #
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import pandas as pd
import numpy as np

dataset_dict = {
'Rainfall': [0.0, 2.0, 7.0, 18.0, 3.0, 3.0, 0.0, 1.0, 0.0, 25.0, 0.0, 18.0, 9.0, 5.0, 0.0, 1.0, 7.0, 0.0, 0.0, 7.0, 5.0, 3.0, 0.0, 2.0, 0.0, 8.0, 4.0, 4.0],
'Temperature': [29.4, 26.7, 28.3, 21.1, 20.0, 18.3, 17.8, 22.2, 20.6, 23.9, 23.9, 22.2, 27.2, 21.7, 27.2, 23.3, 24.4, 25.6, 27.8, 19.4, 29.4, 22.8, 31.1, 25.0, 26.1, 26.7, 18.9, 28.9],
'Humidity': [85.0, 90.0, 78.0, 96.0, 80.0, 70.0, 65.0, 95.0, 70.0, 80.0, 70.0, 90.0, 75.0, 80.0, 88.0, 92.0, 85.0, 75.0, 92.0, 90.0, 85.0, 88.0, 65.0, 70.0, 60.0, 95.0, 70.0, 78.0],
'WindSpeed': [2.1, 21.2, 1.5, 3.3, 2.0, 17.4, 14.9, 6.9, 2.7, 1.6, 30.3, 10.9, 3.0, 7.5, 10.3, 3.0, 3.9, 21.9, 2.6, 17.3, 9.6, 1.9, 16.0, 4.6, 3.2, 8.3, 3.2, 2.2],
'Play': ['No', 'No', 'Yes', 'Yes', 'Yes', 'No', 'Yes', 'No', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'No', 'No', 'Yes', 'Yes', 'No', 'No', 'No', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'No', 'Yes']
}
df = pd.DataFrame(dataset_dict)

# Set feature matrix X and target vector y
X, y = df.drop(columns='Play'), df['Play']

# Split the data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.5, shuffle=False)
print(pd.concat([X_train, y_train], axis=1), end='\n\n')
print(pd.concat([X_test, y_test], axis=1))

Gaussian Naive Bayes works with continuous data, assuming each feature follows a Gaussian (normal) distribution.

  1. Calculate the probability of each class in the training data.
  2. For each feature and class, estimate the mean and variance of the feature values within that class.
  3. For a new instance:
    a. For each class, calculate the probability density function (PDF) of each feature value under the Gaussian distribution of that feature within the class.
    b. Multiply the class probability by the product of the PDF values for all features.
  4. Predict the class with the highest resulting probability.
Gaussian Naive Bayes uses the normal distribution to model the likelihood of different feature values for each class. It then combines these likelihoods to make a prediction.

Transforming non-Gaussian distributed data

Remember that this algorithm naively assume that all the input features are having Gaussian/normal distribution?

Since we are not really sure about the distribution of our data, especially for features that clearly don’t follow a Gaussian distribution, applying a power transformation (like Box-Cox) before using Gaussian Naive Bayes can be beneficial. This approach can help make the data more Gaussian-like, which aligns better with the assumptions of the algorithm.

All columns are scaled using Power Transformation (Box-Cox Transformation) and then standardized.
from sklearn.preprocessing import PowerTransformer

# Initialize and fit the PowerTransformer
pt = PowerTransformer(standardize=True) # Standard Scaling already included
X_train_transformed = pt.fit_transform(X_train)
X_test_transformed = pt.transform(X_test)

Now we are ready for the training.

1. Class Probability Calculation: For each class, calculate its probability: (Number of instances in this class) / (Total number of instances)

from fractions import Fraction

def calc_target_prob(attr):
total_counts = attr.value_counts().sum()
prob_series = attr.value_counts().apply(lambda x: Fraction(x, total_counts).limit_denominator())
return prob_series

print(calc_target_prob(y_train))

2. Feature Probability Calculation : For each feature and each class, calculate the mean (μ) and standard deviation (σ) of the feature values within that class using the training data. Then, calculate the probability using Gaussian Probability Density Function (PDF) formula.

For each weather condition, determine the mean and standard deviation for both “YES” and “NO” instances. Then calculate their PDF using the PDF formula for normal/Gaussian distribution.
The same process is applied to all of the other features.
def calculate_class_probabilities(X_train_transformed, y_train, feature_names):
classes = y_train.unique()
equations = pd.DataFrame(index=classes, columns=feature_names)

for cls in classes:
X_class = X_train_transformed[y_train == cls]
mean = X_class.mean(axis=0)
std = X_class.std(axis=0)
k1 = 1 / (std * np.sqrt(2 * np.pi))
k2 = 2 * (std ** 2)

for i, column in enumerate(feature_names):
equation = f"{k1[i]:.3f}·exp(-(x-({mean[i]:.2f}))²/{k2[i]:.3f})"
equations.loc[cls, column] = equation

return equations

# Use the function with the transformed training data
equation_table = calculate_class_probabilities(X_train_transformed, y_train, X.columns)

# Display the equation table
print(equation_table)

3. Smoothing: Gaussian Naive Bayes uses a unique smoothing approach. Unlike Laplace smoothing in other variants, it adds a tiny value (0.000000001 times the largest variance) to all variances. This prevents numerical instability from division by zero or very small numbers.

Given a new instance with continuous features:

1. Probability Collection:
For each possible class:
· Start with the probability of this class occurring (class probability).
· For each feature in the new instance, calculate the probability density function of that feature within the class.

For ID 14, we calculate the PDF each of the feature for both “YES” and “NO” instances.

2. Score Calculation & Prediction:
For each class:
· Multiply all the collected PDF values together.
· The result is the score for this class.
· The class with the highest score is the prediction.

from scipy.stats import norm

def calculate_class_probability_products(X_train_transformed, y_train, X_new, feature_names, target_name):
classes = y_train.unique()
n_features = X_train_transformed.shape[1]

# Create column names using actual feature names
column_names = [target_name] + list(feature_names) + ['Product']

probability_products = pd.DataFrame(index=classes, columns=column_names)

for cls in classes:
X_class = X_train_transformed[y_train == cls]
mean = X_class.mean(axis=0)
std = X_class.std(axis=0)

prior_prob = np.mean(y_train == cls)
probability_products.loc[cls, target_name] = prior_prob

feature_probs = []
for i, feature in enumerate(feature_names):
prob = norm.pdf(X_new[0, i], mean[i], std[i])
probability_products.loc[cls, feature] = prob
feature_probs.append(prob)

product = prior_prob * np.prod(feature_probs)
probability_products.loc[cls, 'Product'] = product

return probability_products

# Assuming X_new is your new sample reshaped to (1, n_features)
X_new = np.array([-1.28, 1.115, 0.84, 0.68]).reshape(1, -1)

# Calculate probability products
prob_products = calculate_class_probability_products(X_train_transformed, y_train, X_new, X.columns, y.name)

# Display the probability product table
print(prob_products)

For this particular dataset, this accuracy is considered quite good.
from sklearn.naive_bayes import GaussianNB
from sklearn.metrics import accuracy_score

# Initialize and train the Gaussian Naive Bayes model
gnb = GaussianNB()
gnb.fit(X_train_transformed, y_train)

# Make predictions on the test set
y_pred = gnb.predict(X_test_transformed)

# Calculate the accuracy
accuracy = accuracy_score(y_test, y_pred)

# Print the accuracy
print(f"Accuracy: {accuracy:.4f}")

GaussianNB is known for its simplicity and effectiveness. The main thing to remember about its parameters is:

  1. priors: This is the most notable parameter, similar to Bernoulli Naive Bayes. In most cases, you don’t need to set it manually. By default, it’s calculated from your training data, which often works well.
  2. var_smoothing: This is a stability parameter that you rarely need to adjust. (the default is 0.000000001)

The key takeaway is that this algoritm is designed to work well out-of-the-box. In most situations, you can use it without worrying about parameter tuning.

Pros:

  1. Simplicity: Maintains the easy-to-implement and understand trait.
  2. Efficiency: Remains swift in training and prediction, making it suitable for large-scale applications with continuous features.
  3. Flexibility with Data: Handles both small and large datasets well, adapting to the scale of the problem at hand.
  4. Continuous Feature Handling: Thrives with continuous and real-valued features, making it ideal for tasks like predicting real-valued outputs or working with data where features vary on a continuum.

Cons:

  1. Independence Assumption: Still assumes that features are conditionally independent given the class, which might not hold in all real-world scenarios.
  2. Gaussian Distribution Assumption: Works best when feature values truly follow a normal distribution. Non-normal distributions may lead to suboptimal performance (but can be fixed with Power Transformation we’ve discussed)
  3. Sensitivity to Outliers: Can be significantly affected by outliers in the training data, as they skew the mean and variance calculations.

Gaussian Naive Bayes stands as an efficient classifier for a wide range of applications involving continuous data. Its ability to handle real-valued features extends its use beyond binary classification tasks, making it a go-to choice for numerous applications.

While it makes some assumptions about data (feature independence and normal distribution), when these conditions are met, it gives robust performance, making it a favorite among both beginners and seasoned data scientists for its balance of simplicity and power.

import pandas as pd
from sklearn.naive_bayes import GaussianNB
from sklearn.preprocessing import PowerTransformer
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split

# Load the dataset
dataset_dict = {
'Rainfall': [0.0, 2.0, 7.0, 18.0, 3.0, 3.0, 0.0, 1.0, 0.0, 25.0, 0.0, 18.0, 9.0, 5.0, 0.0, 1.0, 7.0, 0.0, 0.0, 7.0, 5.0, 3.0, 0.0, 2.0, 0.0, 8.0, 4.0, 4.0],
'Temperature': [29.4, 26.7, 28.3, 21.1, 20.0, 18.3, 17.8, 22.2, 20.6, 23.9, 23.9, 22.2, 27.2, 21.7, 27.2, 23.3, 24.4, 25.6, 27.8, 19.4, 29.4, 22.8, 31.1, 25.0, 26.1, 26.7, 18.9, 28.9],
'Humidity': [85.0, 90.0, 78.0, 96.0, 80.0, 70.0, 65.0, 95.0, 70.0, 80.0, 70.0, 90.0, 75.0, 80.0, 88.0, 92.0, 85.0, 75.0, 92.0, 90.0, 85.0, 88.0, 65.0, 70.0, 60.0, 95.0, 70.0, 78.0],
'WindSpeed': [2.1, 21.2, 1.5, 3.3, 2.0, 17.4, 14.9, 6.9, 2.7, 1.6, 30.3, 10.9, 3.0, 7.5, 10.3, 3.0, 3.9, 21.9, 2.6, 17.3, 9.6, 1.9, 16.0, 4.6, 3.2, 8.3, 3.2, 2.2],
'Play': ['No', 'No', 'Yes', 'Yes', 'Yes', 'No', 'Yes', 'No', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'No', 'No', 'Yes', 'Yes', 'No', 'No', 'No', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'No', 'Yes']
}

df = pd.DataFrame(dataset_dict)

# Prepare data for model
X, y = df.drop('Play', axis=1), (df['Play'] == 'Yes').astype(int)

# Split data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, shuffle=False)

# Apply PowerTransformer
pt = PowerTransformer(standardize=True)
X_train_transformed = pt.fit_transform(X_train)
X_test_transformed = pt.transform(X_test)

# Train the model
nb_clf = GaussianNB()
nb_clf.fit(X_train_transformed, y_train)

# Make predictions
y_pred = nb_clf.predict(X_test_transformed)

# Check accuracy
accuracy = accuracy_score(y_test, y_pred)
print(f"Accuracy: {accuracy:.4f}")



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12Oct

Sales Engineer – Mid Market at Samsara – Remote – US


Who we are

Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale.

Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, Equipment Monitoring, and Site Visibility. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term.

About the role:

As a Sales Engineer at Samsara, you’d be an integral part of a diverse team working to help modernize essential industries through the application of cutting edge IoT solutions.  Your work would directly contribute to a cleaner, more efficient and productive supply chain by creating safer roadways, reducing fuel consumption and emissions, and providing a consolidated platform for connecting operations.  Our daily customer engagements include conversations around how IoT can positively impact logistics management, workplace safety programs, fleet maintenance strategies, global asset management, and regulatory compliance.  This means a successful SE at Samsara will develop a thorough understanding of the application of IoT hardware and sensors, hands-on hardware installation strategies, managing data collection over carrier networks, presenting a robust cloud infrastructure, and building third-party system integrations (via our open API) to ensure the best technical solution is presented to Samsara customers.

This is a remote position, open to candidates located in the United States, within the Eastern or Central Time-Zone. Relocation assistance will not be provided for this role. 

You should apply if: 

  • You want to impact the industries that run our world: Your efforts will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.
  • You have an innate curiosity about how businesses work: One day you’ll meet with someone in waste management and the next you may be learning about the inner workings of a food distribution center. Our top sales team members seek to learn the ins and outs of the businesses they support in order to make a larger impact. 
  • You build genuine relationships with your customers: The industries we serve have relied on pen-and-paper solutions for years and haven’t been met with the type of technology we offer. Our customer’s value earned trust and human relationships built over time.
  • You want to be with the best: Samsara’s high-performance culture means you’ll be surrounded by the best and challenged to go farther than you have before. 
  • You are a team player: At Samsara, sales is a team sport. We help each other out by sharing best practices and focusing on winning as a team.

In this role, you will: 

  • Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices
  • Become an expert on Samsara products: where the rubber of cutting-edge tech (IoT, AI, computer vision) meets the road of driving digital transformation for physical operations.
  • Articulate to prospects how businesses like theirs use Samsara today to solve challenges common to their industry.
  • Deliver the work products that get deals done.  Think discoveries, demonstrations, value assessments, proof of concept implementations, etc.
  • Walk installers through any scenario, explaining best practices for installing Samsara products and helping build deployment plans.
  • Write scripts against our open API that solve real-world problems for companies that deliver essential services (for example), and document them for your fellow SE’s to use.
  • Open the door for deeper entrenchment into accounts (integration, upsell, cross sell) by becoming a consultant to your customers.
  • Act as a liaison between Samsara’s product and sales teams, translating technical feedback and enrolling the right customers in our beta programs.

Minimum requirements for the role:

  • Bachelors’ of Science degree from a 4 year accredited university 
  • 2+ years experience working with customers in a pre-sales, customer success, or customer/product support capacity
  • Ability to influence stakeholders based on your technical sales acumen and a solid understanding of business processes and change management
  • Ability to explain complex technical concepts to non-technical audiences
  • Previous experience managing hardware and/or software product evaluations
  • Basic understanding of electronics and electrical systems
  • Experience with the following concepts: technical consulting, cloud software, cloud-connected hardware, computer networking, business systems integration, automation and control systems
  • Must be located within and authorized to work in the United States

An ideal candidate also has:

  • Bachelors’ of Science degree or advanced education in Electrical Engineering, Computer Science, Mechanical Engineering, Industrial Engineering, or related discipline
  • Work experience in task automation scripting and transferring data between systems using Bash, Python, JavaScript, or equivalent language
  • Work experience building solutions leveraging open API’s
  • Understanding of vehicle diagnostic systems, including Controller Area Networks (CAN bus) and Power Take Off (PTO) applications
  • Hobbyist interest in working with things driven by electronic systems (car audio installation/classic car restoration, home automation, building things with raspberry pi, arduino, etc.)
  • Consistent track record of success selling complex technical solutions through strategic sales cycles.

Samsara’s Compensation Philosophy: Samsara’s compensation program is designed to deliver Total Direct Compensation (based on role, level, and geography) that is at or above market. We do this through our base salary + bonus/variable + restricted stock unit awards (RSUs) for eligible roles.  For eligible roles, a new hire RSU award may be awarded at the time of hire, and additional RSU refresh grants may be awarded annually. 

We pay for performance, and top performers in eligible roles may receive above-market equity refresh awards which allow employees to achieve higher market positioning.

The range of annual on-target earnings (OTE) range for full-time employees for this position is below. Please note that OTE pay may vary depending on factors including your city of residence, job-related knowledge, skills, and experience.$92,880—$156,100 USD

At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems. We are committed to increasing diversity across our team and ensuring that Samsara is a place where people from all backgrounds can make an impact.

Benefits

Full time employees receive a competitive total compensation package along with employee-led remote and flexible working, health benefits, Samsara for Good charity fund, and much, much more. Take a look at our Benefits site to learn more.

Accommodations 

Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email

ac********************@sa*****.com











or click here if you require any reasonable accommodations throughout the recruiting process.

Flexible Working 

At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable.

Fraudulent Employment Offers

Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in ‘@samsara.com’ or ‘@us-greenhouse-mail.io’. For more information regarding fraudulent employment offers, please visit our blog post here.



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