Enabling Areas - Information Technology - Deputy Manager - AI Solutions - Mumbai
- Job requisition ID : 100894
- Location: Mumbai - Commerz III
- Entity: Deloitte Shared Services India LLP
The team
The Enabling Areas – Information Technology team is responsible for building & maintaining different applications for Deloitte that focuses on providing employee experience.
Your work profile
Key Responsibilities
- Lead stakeholder interviews, workshops, and process walkthroughs to elicit and document functional/non-functional requirements (BRDs, user stories, acceptance criteria).
- Perform gap analysis, feasibility assessments, and traceability from business goals to product features.
- Shape product vision and roadmap for AI features; prioritize backlogs based on value, feasibility, and risk.
- Run Agile ceremonies (refinement, sprint planning, reviews) and maintain clear release plans and OKRs.
- Translate use cases into LLM/GenAI solutions (e.g., retrieval-augmented generation, prompt engineering, evaluation criteria) with DS/ML engineers.
- Coordinate data availability, model monitoring, and governance (security, privacy, cost/performance) with platform teams.
- Demo increments, validate requirements, and manage UAT with business users; drive adoption and training assets (playbooks, guides).
- Communicate status, risks, and mitigation plans to leadership; support post-launch analysis and continuous improvement.
- Maintain clear artefacts (journey maps, process flows, personas, wireframes) and QA/test plans in partnership with QA leads.
Key skills required
Skills (Must-have)
- Strong BA toolkit (elicitation, analysis, documentation, UAT).
- Product tools (Jira/ADO/Confluence), and proficiency in MS Office for analysis and communication.
- AI literacy: familiarity with LLMs/GenAI concepts, RAG patterns, evaluation/guardrails, and data governance.
- Collaboration across Data Science, Engineering, UX; excellent stakeholder communication.
Preferred Exposure
- Hands-on with prompt design, GenAI evaluation, vector databases, or model lifecycle (training, deployment, monitoring).
- Experience in cloud platforms (AWS/Azure/GCP) and modern data/ML tooling.
Success Metrics (KPIs)
- Requirement lead time (from intake to signed-off user stories), backlog health, and sprint goal attainment.
- Feature adoption (usage, satisfaction), model performance & cost (for AI features), and defect escape rate/UAT pass-rate.
Qualifications
- Master's or Ph.D. degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
- Minimum of 5+ years of proven experience as a Data Scientist with a focus on NLP and 2 years on Gen AI, preferably in industry or research settings.
- Strong knowledge of NLP techniques and algorithms, including text preprocessing, feature extraction, and supervised and unsupervised learning methods.
- Proficiency in programming languages such as Python or R, and libraries such as NLTK, spaCy, scikit-learn, and TensorFlow/PyTorch for NLP.
- Familiarity with data visualization tools such as Matplotlib, Seaborn, or Plotly.
- Experience with containerization and orchestration technologies such as Docker and Kubernetes.
- Basic understanding of system design and ML-Ops practices.
- Excellent problem-solving skills and analytical thinking.
- Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.
- Proven ability to manage multiple projects simultaneously and meet deadlines in a fast-paced environment.
