 
        
        Role: Data Scientist / Data Analyst — Property Use-Case Modelling
Company: adema.ai (UK PropTech)
Location: Remote-friendly (UK/EU time zones) • Full-time
Mission
Help us add new property use-case analyses (e.g., Residential, Social Housing, Commercial, Care, STR, EV Charging, Data Centres). You’ll research and source datasets, build models that infer demand/supply and revenue potential at the most local level possible, and ship them into our product.
What you’ll do
 * Map each “use case” data landscape: Identify, evaluate and acquire structured sources (e.g., prices, rents, demographics, planning, POIs, transport, connectivity) and useful unstructured sources (local plans, market reports, PDFs). Track licence terms and provenance.
 * Engineer geospatial & temporal features: Join/clean data, spatially downscale/coalesce (e.g., LA → LSOA/sector/property) using proxies (prices, comps, time-series trends, neighbourhood features, travel times).
 * Build predictive/forecast models: Estimate demand, supply, pricing/rent & revenue; quantify uncertainty; design robust validation and back-testing.
 * Productionise your work: Persist outputs in Postgres/PostGIS, expose via GraphQL; implement services in Go or Python; write clear SQL views, tests and docs; monitor data quality and model drift.
 * Extract signal from unstructured data: Scrape/download reports, parse tables/figures, apply LLM-assisted extraction where useful; convert to structured features.
 * Collaborate across the stack:
 * 
 * With Product to define success metrics and MVP scope per genre.
 * With Backend to integrate pipelines/APIs.
 * With Frontend/AI teams to shape GraphQL queries and agent/tool schemas.
 * Ship iteratively: Prioritise “easier” genres first (Residential, Commercial), then expand to specialised sectors. Document assumptions and limitations.
What you’ve done
 * 3+ years in Data Science / Analytics (or 2+ with a strong portfolio) delivering models into production.
 * Strong Python (pandas/numpy/scikit-learn; XGBoost/LightGBM; basic PyTorch a plus) and SQL.
 * Solid geospatial skills (PostGIS/GeoPandas/QGIS) and time-series/forecasting know-how.
 * ETL/ELT and data wrangling at scale; comfort with scraping and PDF/table extraction.
 * Good software practice: Git, containers, CI/CD, testing, clear documentation.
 * Product mindset: bias to ship, explain results simply, track impact.
Nice to have
 * Go, GraphQL, dbt, Airflow/Dagster, FastAPI; Azure.
 * UK property/economics exposure (Land Registry, EPC, census/ONS, planning, VOA etc.).
 * LLM/AI experience for information extraction or analyst co-pilots.
Success looks like
30 days: Different types of Residential models live in app (Postgres/PostGIS + GraphQL), with documented features, validation and property-level scoring.
Why adema.ai
We’re building the decision layer for UK property — rigorous data, clear modelling, and real-world utility. If you love turning messy datasets into decisive answers, you’ll fit right in.
HOW TO APPLY
Please send your CV to sales@adema.ai and we will come back to you quickly.