Senior Data Scientist - Geospatial AI & Location Intelligence

: 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