- Santriya Technologies is seeking an AI Property Valuation & Market Insights Analyst to produce property market and valuation insights using automated valuation models and AI analytics as decision support, with explicit data quality, assumptions and human review.

- 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:
- Analyze property attributes, comparable evidence, transaction/listing trends and local market drivers.

- Interpret AVM/model outputs, confidence and limitations rather than presenting a model estimate as a formal valuation when it is not one.

- Use AI to summarize local-market evidence and identify comparable candidates, verifying source data.

- Investigate outliers, data quality issues and model disagreement.





- Prepare client/partner/internal market insight reports with sources and assumptions.

- Monitor model performance and segment bias with data/model teams.

- Protect licensed, personal and confidential property data.

- Escalate cases requiring regulated valuation or specialist surveyor judgement.

- 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:

- Insight turnaround improves
- Model limitations are communicated clearly

- Data quality issues are detected earlier

- Users receive evidence-backed market context

📌 AI Property Valuation & Market Insights Analyst (Chennai)
🏢 Santriya Technologies
📍 Chennai