Website:
nam-info.com
Job details:
Greetings from NAM Info Pvt Ltd,
We have an opportunity for the position below. Please go through the job description. If you are interested in this opportunity, please apply.
JOB TITLE: Tech Product Lead - Data Scientist
SKILL CATEGORY: Data Science
WORK LOCATION: Bangalore location only
WORK PREFERENCE: Hybrid – 3 days' work from office
DURATION: Full-Time Employment
MANDATORY SKILLS: Geospatial AI, Geopandas, Langchain / LlamaIndex, RAG
Experience – 10+ years
Notice Period – Immediate to max 15 days
How many rounds of Interview - 2 rounds
What You Will Do
Location Intelligence & Geospatial AI
• Design and build geospatial models that power Navigator's location scoring, market positioning and demographic analysis capabilities, integrating data from CoStar, labour market sources and third-party geospatial providers
• Develop location-based AI agent capabilities, including the Analytics Agent's real-time market intelligence layer, enabling the platform to surface relevant location insights for any given portfolio scenario
• Build and maintain geospatial data pipelines that ingest, transform and serve location data at the scale required for multi-portfolio analysis — including property-level data, demographic overlays, transport networks and ESG indicators
• Integrate map functionality into the Navigator platform, including synchronised list and map views, property clustering, search and filtering, and data overlays — working closely with engineering to ensure performance and usability
• Evaluate and onboard geospatial data sources, including CoStar and other third-party providers, assessing data quality, coverage and commercial terms for inclusion in the platform
AI Agent Development & Data Science
• Design, train and validate machine learning models that underpin Navigator's multi-criteria scoring framework — including Cost Optimisation, ESG/Sustainability, Talent Accessibility, Market Positioning and Risk Mitigation axes
• Own the data science architecture for the AI Scenario Agent, developing the model logic that generates and evaluates alternate portfolio strategies based on client-defined criteria and weighted priorities
• Build RAG pipelines and document intelligence capabilities that enable agents to reason over lease documents, market reports and financial data — directly relevant to the Lease Admin Agents programme
• Define evaluation frameworks and guardrails for AI output quality, including bias detection, accuracy validation and responsible AI compliance — ensuring model outputs are commercially credible and production-ready
• Monitor and optimise model performance in production, using NPS data from Pendo and user feedback from Optimal Workshop to identify where model outputs are falling short and iterating accordingly
Product Strategy & Stakeholder Collaboration
• Act as the data science product authority, translating business requirements from deep dive workshops and SME sessions into data science specifications that engineering teams can build against
• Own the analytical product roadmap, defining how location intelligence, geospatial AI and data science capabilities will evolve across Navigator's development phases — from current MVP through to future iterations
• Contribute to the AWS platform selection decision, specifically assessing the geospatial and ML infrastructure capabilities of AWS AgentCore and related services against Navigator's analytical requirements
• Participate in Critical Design Reviews (CDR), providing data science and geospatial expertise to ensure architectural decisions support the analytical capabilities the product requires
• Present model outputs, methodology and validation findings to senior stakeholders and client-facing audiences in clear, non-technical language
Governance & Standards
• Maintain documentation on model methodology, data sources, validation outcomes and geospatial data lineage in Confluence — supporting CDR compliance and responsible AI governance
• Ensure all geospatial and AI models comply with JLL's data governance policies, applicable data privacy regulations, and the AI Terms Addendum obligations under vendor contracts
• Support token cost management and optimisation across AI agent interactions, working with engineering to ensure the analytical layer operates efficiently at scale
What We Are Looking For
Essential
• 10+ years of hands-on data science experience, with at least 2 years working with geospatial data, location intelligence or spatial analytics in a product or platform environment
• Strong Python proficiency, including geospatial libraries such as GeoPandas, Shapely, Folium, PostGIS or equivalent
• Demonstrated experience building and deploying AI agents or LLM-based systems in production, including RAG design, agent orchestration and output evaluation
• Experience designing multi-criteria scoring and weighting frameworks for complex decision support applications
• Proficiency building and managing data pipelines on cloud infrastructure, ideally AWS or Azure
• Experience working with commercial real estate, demographic or labour market data sources — including CoStar, CBRE, or equivalent
• Strong product mindset — able to translate data science outputs into user-facing value and communicate model behaviour to non-technical stakeholders clearly
• Ability to operate across the full delivery cycle — from requirements and architecture through to production validation and iteration
Desirable
• Experience with AWS geospatial services, SageMaker or AWS AgentCore for production ML deployment
• Familiarity with ESG data frameworks, carbon emissions modelling or sustainability scoring methodologies
• Experience in real estate, financial services or enterprise SaaS environments
• Knowledge of vector databases, embeddings and semantic search for geospatial or document intelligence use cases
• Experience with Pendo, Optimal Workshop or equivalent product analytics and user research tools
• Familiarity with map rendering libraries and spatial visualisation tools for web applications
• Knowledge of responsible AI frameworks, bias evaluation and model governance for enterprise deployment
Key Technologies
Data Science
Geospatial
AI & Agents
Platform
Python · Pandas · NumPy · Scikit-learn · SQL (Postgres / SQLite)
GeoPandas · Shapely · PostGIS · Folium · CoStar API
LangChain / LlamaIndex · RAG · Vector DBs · AWS AgentCore · Claude / OpenAI
AWS / Azure · Confluence · Jira · Pendo · Optimal Workshop
Click on Apply to know more.
