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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: 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 at meetups. A friendly chat can sometimes lead to job opportunities that aren’t even advertised yet.
✨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 a role like Data Scientist/Analyst.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. We want you to feel confident discussing your past projects and how they relate to the property use-case modelling at adema.ai.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
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 / Data 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 examples of projects where you've built models or worked with datasets. If you've tackled property use-case analyses before, let us know! This helps us understand your hands-on experience and problem-solving skills.
Keep It Clear and Concise: When writing your application, clarity is key. Use straightforward language and avoid jargon unless necessary. We appreciate a well-structured application that gets straight to the point—just like we do with our data!
Apply Through Our Website: 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 from us. We can't wait to hear from you!
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 estimate demand or pricing. If you can, demonstrate your understanding of tools like Python and SQL during the conversation.
✨Highlight Collaboration Experience
This role requires working across different teams, so be ready to share examples of how you've collaborated with product, backend, or frontend teams in the past. Discussing your approach to defining success metrics and integrating pipelines will illustrate your team-oriented mindset.
✨Ask Insightful Questions
Prepare thoughtful questions about adema.ai's current projects and future goals. Inquire about their approach to model validation or how they handle data quality. This not only shows your interest but also helps you gauge if the company aligns with your career aspirations.