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- Tasks: Transform messy datasets into actionable insights for property use-case modelling.
- Company: Join adema.ai, a leading UK PropTech company revolutionising property analysis.
- Benefits: Enjoy remote-friendly work, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in the property sector with innovative data solutions.
- Qualifications: 3+ years in Data Science/Analytics with strong Python and SQL skills.
- Other info: Collaborative environment with a focus on cutting-edge technology and career advancement.
The predicted salary is between 36000 - 60000 ÂŁ per year.
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.
Data Scientist / Data Analyst employer: SH Proptech Limited
Contact Detail:
SH Proptech Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist / Data Analyst
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or attend local meetups. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and analyses. This is your chance to shine and demonstrate what you can bring to the table, especially for roles like Data Scientist or Analyst.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s mission. For adema.ai, be ready to discuss how you can contribute to their property use-case modelling and data-driven decisions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the team at adema.ai.
We think you need these skills to ace Data Scientist / Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Scientist/Analyst role. Highlight your experience with Python, SQL, and any geospatial tools you've used. We want to see how you can contribute to our mission!
Showcase Your Projects: Include specific projects in your application that demonstrate your ability to build predictive models and work with datasets. If you've tackled similar property use-case analyses before, let us know! We love seeing real-world applications of your skills.
Keep It Clear and Concise: When writing your application, be clear and to the point. Use bullet points where possible to make it easy for us to read. We appreciate straightforward communication, especially when it comes to complex data topics.
Apply Through Our Website: While you can send your CV to sales@adema.ai, we encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates!
How to prepare for a job interview at SH Proptech Limited
✨Know Your Data Inside Out
Before the interview, dive deep into the types of datasets relevant to property use-case modelling. Familiarise yourself with sources like Land Registry and ONS data. Being able to discuss specific datasets and their implications will show your expertise and enthusiasm for the role.
✨Showcase Your Modelling Skills
Prepare to discuss your experience with predictive modelling and how you've applied it in past projects. Bring examples of models you've built, especially those that relate to demand and supply forecasting. This will demonstrate your practical skills and understanding of the job requirements.
✨Brush Up on Geospatial Tools
Since geospatial skills are crucial for this role, make sure you're comfortable discussing tools like PostGIS and GeoPandas. Be ready to explain how you've used these tools to manipulate and analyse spatial data in previous roles.
✨Emphasise Collaboration and Communication
This role requires working across different teams, so highlight your experience in collaborative projects. Share examples of how you've communicated complex data insights to non-technical stakeholders, as this will showcase your ability to fit into their product mindset.