Entity: – Accenture Strategy & Consulting
Team: – Strategy & Consulting – Global Network
Practice: – Responsible AI COE
Title: – Responsible AI Manager
Job location: – Bangalore/Gurgaon/Pune/ Hyderabad/Chennai/Mumbai
The rapid development of AI is creating new opportunities to improve the lives of people around the world, from business to healthcare to education. As a result, it is also raising new questions about the best way to build fairness, interpretability, privacy and security into these systems.
The Data and AI revolution is changing everything. It’s everywhere – transforming how we work and play. Join Accenture and help transform leading companies and communities around the world.
Accenture is driving these exciting changes and bringing them to life across 40 industries in more than 120 countries. The sheer scale of our capabilities and client engagements and the way we collaborate with the ecosystem, operate, and deliver value provides an unparalleled opportunity to grow and advance.
Accenture’s S&C Global Network – Data & AI team covers the range of skills, from Strategy, Data Science, Data Architecture, AI Engineering and Visual Insights. When combined with our broader Strategy and Consulting practice, we bring a unique ability to drive end to end business change through the application of Data and AI.
At the forefront of the industry, you’ll help make our Responsible AI vision a reality for clients looking to better serve their customers and operate always-on enterprises. We’re not just focused on increasing revenues – our technologies and innovations are making millions of lives easier and more comfortable. But above all, we’re doing this responsibly and inclusively – to make sure AI technology is used equitably and in a way that is both ethically and technically sound.
Join us and become an integral part of our global Responsible AI team with the credibility, expertise and insight clients depend on. There will never be a typical day at Accenture, but that’s why people love it here. You will be working with famous brands and household names – no worrying about how to explain what you do to your family again!
We are looking for experienced and motivated individuals who will be a part of the Responsible AI Centre of Excellence (COE) within Accenture to join our multi-disciplinary Responsible AI team. We are committed to help people build AI products/solutions/services in a responsible and trustworthy manner.
The ideal candidate should have a strong client-facing consulting background in data science/analytics with an ability to pick up new technologies very quickly. He/she will be passionate about understanding the impact of AI systems on people and society and will have a track record in using tools to undertake assessments such as Fairness/Bias, Explainability, Model Validation and Robustness, to assess model behaviour through a Responsibility lens.
Being a part of Accenture will help you grow both professionally and personally as you help shape our thinking and approaches to Responsible AI, working alongside world-class academics, industry leaders and practitioners. Responsible AI is a key strategic priority for Accenture and we’re looking for the very best in the field to help us meet our ambitious goals in this space.
Responsibilities:
As a client-facing in Responsible AI, you will consult with Accenture’s clients on how to design & develop reliable, effective user-centered AI systems in adherence to general best practices for software systems, together with practices that address responsibility considerations unique to AI & machine learning. You will also be expected to contribute to research on how AI systems can be designed holistically with fairness, interpretability, privacy, security, safety, and robustness built in by design.
As part of our team, you will:
- Be a subject matter expert on technical aspects of Responsible AI & Data
- Collaborate with colleagues to develop best practices, frameworks, tools for scalable implementation of Responsible AI in enterprises
- Conduct research on Responsible AI – policies, principles, issues, risk identification, risk remediation, regulatory requirements, latest trends etc.
- Bring a strong conceptual understanding of Responsible AI, principles & tools with experience of using these tools in close collaboration with internal and external stakeholders/clients
- Evaluate and implement technical best practices and tools for fairness, explainability, transparency, accountability, and other relevant aspects of Responsible AI
- Develop a clear understanding of client’s business issues to adopt the best approach to implement the Responsible AI Framework
- Establish a consistent and collaborative presence by partnering with clients to understand the wider business goals, objectives & competitive constraints
- Provide thought leadership by publishing in public forums/conferences/blogs on Responsible AI products, research or developments
- Leading diverse and well-qualified RAI team.
Skillset Requirements:
- Education: – PhD / Masters / Bachelor’s degree in Statistics / Economics / Mathematics /Computer Science / Physics or related disciplines from Premier Colleges in India or Abroad. Specialization in Data Science.
Must Have
- 7+ years of Hands-on Data science experience in solving real life complex business problems
- Minimum 3 years’ experience in enhancing AI systems to meet Responsible AI principles – Explainability, Fairness, Accountability, etc.
- Passionate about understanding the impact of AI systems on people and society
- Hands-on experience of using techniques such as data bias testing (e.g. for under-represented groups, proxy variables, recall bias, skew etc), Explainability (e.g. SHAP values, LIME), sensitivity testing, repeatability and similar to understand model limitations.
- Demonstrated experience in writing reports that summarize analysis / assessments into simple and concise actionable points
- Strong conceptual knowledge and practical experience in the Development, Validation, and Deployment of ML/AL models such as:
- Supervised Learning – regression, classification techniques
- Unsupervised Learning – clustering techniques
- Recommender Systems
- Reinforcement Learning
- Deep Learning – Sequence models (RNN, GRU, LSTM etc.), CNN, GAN etc
- Econometric models
- Exploratory Data analysis, Hypothesis testing etc.
- Comfortable in ingestion of technical whitepapers, legal policies, government regulations etc. in relation into Responsible AI and work with Academic partners to convert them into practice
- Ability to learn and develop new methods, strategies and frameworks to proactively identify potential loopholes.
- Comfortable with ambiguity, believe in first principles and have the skill to transform broad ideas into action plans
- Excellent written and verbal communication skills with ability to clearly communicate ideas and results to both technical and non-technical business audience, such as senior leaders
- Good time management skills to manage day-to-day work progress and ensure timely and high-quality deliverables
- Self-motivated with ability to work independently across multiple projects and set priorities and Strong analytical bent of mind.
Good to have
- Cloud Certifications (Azure / AWS / GCP)
- Knowledge of AWS SageMaker Clarify / Azure Responsible ML and Fairlearn SDK / GCP AI Explanations
- Experience in Chatbot Analytics, Web Crawling
- Experience in MLOps tools like MLflow or Kubeflow
- Knowledge of cybersecurity, vulnerability assessment, risk remediation etc.
Equal Employment Opportunity Statement
All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.
Accenture is committed to providing veteran employment opportunities to our service men and women.
