Jones Lang LaSalle
real estate
TechProductLead—DataScientist
“Tech Product Lead — Data Scientist at Jones Lang LaSalle. Skills: Location Intelligence, Geospatial AI, Data Science, AI Agent Development, Product Strategy. Design and build geospatial models. Develop location-based AI agent capabilities”
What You'll Achieve.
production-grade outputs that directly inform client-facing AI recommendations; model outputs are commercially credible and production-ready; analytical engine that powers decisions worth billions in real estate value
Industry & Context.
model complex real estate portfolio scenarios; evaluate strategic options; make data-driven decisions at scale; understand and reason about location; reason over lease documents, market reports and financial data; reasoning about location
What They're Looking For.
Must Have
5+ years of hands-on data science experience, at least 2 years working with geospatial data, location intelligence or spatial analytics in a product or platform environment, Python proficiency, building and managing data pipelines on cloud infrastructure, product mindset, Ability to operate across the full delivery cycle
Nice to Have
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
What You'll Do.
Design and build geospatial models
Develop location-based AI agent capabilities
Build and maintain geospatial data pipelines
Integrate map functionality into the Navigator platform
Evaluate and onboard geospatial data sources
train and validate machine learning models
Own the data science architecture for the AI Scenario Agent
Build RAG pipelines and document intelligence capabilities
Define evaluation frameworks and guardrails for AI output quality
Monitor and optimise model performance in production
Act as the data science product authority
Own the analytical product roadmap
Contribute to the AWS platform selection decision
Participate in Critical Design Reviews (CDR)
Present model outputs
methodology and validation findings
Maintain documentation on model methodology
validation outcomes and geospatial data lineage
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
How You'll Work.
Team & Collaboration
working directly with engineering, product and design teams; translating business requirements from deep dive workshops and SME sessions into data science specifications that engineering teams can build against; working with engineering to ensure the analytical layer operates efficiently at scale
Communication Scope
communicate model behaviour to non-technical stakeholders clearly; Present model outputs, methodology and validation findings to senior stakeholders and client-facing audiences in clear, non-technical language
Process & Methodology
analytical product roadmap, development phases
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