Senior Data Scientist - Geospatial AI & Location Intelligence

Job Description :

Immediate joiners or less than 30 days notice period.

Key Responsibilities :Location Intelligence & Geospatial AI :

• Design and develop geospatial models for location scoring, market positioning, demographic analysis and portfolio decision support.

• Build location-based AI agent capabilities that surface real-time market and location insights for portfolio scenarios.

• Develop scalable geospatial data pipelines covering property data, demographic overlays, transport networks, labour-market data and ESG indicators.

• Support map-based product functionality, including synchronized list/map views, clustering, search, filtering and spatial data overlays.

• Evaluate and onboard third-party geospatial and commercial real-estate data sources based on quality, coverage and usability.

AI Agents, Machine Learning & Data Science :

• Design, train and validate models for multi-criteria scoring across cost, sustainability, talent accessibility, market positioning and risk.

• Own the data-science architecture for AI-driven scenario generation and evaluation using client-defined criteria and weighted priorities.

• Build RAG pipelines and document-intelligence capabilities for reasoning over lease documents, market reports and financial data.

• Define evaluation frameworks and guardrails covering accuracy, bias detection, responsible AI and commercial credibility.

• Monitor and improve production models using product analytics, NPS signals and structured user feedback.

Product Strategy & Stakeholder Collaboration :

• Translate business workshops and SME inputs into clear data-science specifications for engineering teams.

• Own the analytical roadmap for location intelligence, geospatial AI and data-science capabilities from MVP through future releases.

• Assess cloud geospatial and ML services and contribute to platform and architectural decisions.

• Participate in design reviews and present model methodology, outputs and validation findings to technical and non-technical stakeholders.

Governance & Standards :

• Maintain model methodology, data-source, validation and geospatial lineage documentation.

• Ensure compliance with data governance, privacy, responsible AI and applicable vendor obligations.

• Work with engineering to manage and optimise AI-agent token usage and operating costs at scale.

Essential Requirements :

• 10+ years of hands-on data-science experience, including at least 2 years in geospatial data, location intelligence or spatial analytics within a product/platform environment.

• Strong Python expertise with GeoPandas, Shapely, Folium, PostGIS or equivalent geospatial technologies.

• Production experience building AI agents or LLM-based systems, including RAG, agent orchestration and output evaluation.

• Experience designing multi-criteria scoring and weighting frameworks for complex decision-support applications.

• Strong experience building and managing cloud data pipelines, preferably on AWS or Azure.

• Exposure to commercial real-estate, demographic or labour-market datasets from recognized industry providers.

• Strong product mindset and ability to explain model behaviour and business impact to non-technical stakeholders.

• Ability to work across requirements, architecture, development, production validation and continuous improvement.

Mandatory Technical Competencies :

• Geospatial AI and Location Intelligence

• GeoPandas

• LangChain or LlamaIndex

• RAG (Retrieval-Augmented Generation)

Desirable Skills :

• AWS geospatial services, SageMaker or agent-based ML deployment services.

• ESG frameworks, carbon-emissions modelling or sustainability scoring.

• Experience in commercial real estate, financial services or enterprise SaaS.

• Vector databases, embeddings and semantic search for geospatial or document-intelligence use cases.

• Product analytics, user-research tools, web map rendering and spatial visualisation.

• Responsible AI frameworks, bias evaluation and enterprise model governance