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