- Santriya Technologies is seeking an AI Workforce Analytics Consultant to use workforce, skills and recruitment data with AI analytics to help clients plan capacity, skills, hiring and redeployment while maintaining privacy, explainability and human decision ownership.

- Product & documentation operating model: You will be assigned one or more company products, client solutions or operational services.

- The approved product documentation, SOPs, policies, process maps, knowledge articles, release notes, controls, scripts and AI runbooks are the source of truth.

- Use only approved enterprise AI tools to retrieve, summarize, draft, classify, prioritize or automate work.

- Validate material AI outputs against current documentation and authoritative system data, record exceptions, and escalate conflicts or missing guidance.

- Do not invent product features, prices, customer entitlements, engineering limits, regulatory positions or safety instructions.

Key Responsibilities:

- Define workforce questions, metrics and decision needs with business and HR leaders.

- Analyze headcount, skills, demand, attrition, hiring funnel, productivity and capacity data.

- Use AI to accelerate segmentation, summarization and scenario generation, validating statistical and business logic.

- Build skills taxonomies and supply/demand views with explicit confidence and data limitations.





- Create dashboards and executive recommendations tied to measurable outcomes.

- Avoid using sensitive attributes or opaque models for individual employment decisions.

- Partner with recruitment, learning, finance and delivery leaders on actions.

- Measure outcomes and update assumptions over time.

- AI-enabled ways of working:

- Use approved GenAI copilots, enterprise search/RAG, analytics and workflow agents to reduce repetitive work and improve decision preparation.

- Keep prompts, outputs and automated actions within approved data-access, confidentiality and retention rules.

- Correct inaccurate summaries, classifications or recommendations before they become customer, operational or system records.

- Feed recurring AI errors, knowledge gaps and process friction into product, documentation and control improvement.

- Human accountability: AI is a copilot, not the accountable decision-maker.

- The role holder remains responsible for judgement, quality, privacy, security and appropriate escalation.

- Credit, fraud blocking, legal/regulatory, financial advice, safety-critical, clinical, employment and other high-impact decisions must follow delegated authority and required human review.

- Success Measures:
- Workforce decisions become more evidence-based

- Skills gaps are identified earlier

- Planning scenarios are transparent
- People-data governance remains solid

📌 AI Workforce Analytics Consultant (Chennai)
🏢 Santriya Technologies
📍 Chennai