Overview
We’re looking for a Head of Data Science to own and build our entire data science function. This is a hands-on role where you’ll mine, analyze, and experiment with wild data sources—from mobile signals to social trends—to predict where the best investments will be. You’ll be leading a small team (for now) and scaling it as we grow. If you love data, real estate, and making things happen, this role is for you.
Key responsibilities
- Own the entire data science lifecycle – from raw data collection to production-ready machine learning models.
- Lead and scale a data science team – starting with a small team of 2, with plans to grow.
- Design and implement predictive models – focused on real estate trends, pricing, rent forecasts, and investment opportunities.
- Collaborate with R&D to integrate machine learning models into our real estate investment platform.
- Collaborate with R&D to integrate machine learning models into our real estate investment platform.
- Make data science a core business function – working directly with leadership to influence company strategy.
- Own deployment & optimization – working with engineers to ensure models are robust, scalable, and accurate in production.
- Develop visualization tools that translate complex data into actionable insights for investors.
Required experience
- 5+ years in Data Science, Machine Learning, or AI with experience in end-to-end model development.
- Proven leadership experience – managing and scaling data teams.
- Strong Python expertise – Pandas, NumPy, Jupyter, and working with data frames, merging, grouping, processing with lambdas, etc.
- SQL proficiency – complex joins, aggregations, optimizing queries.
- Machine learning expertise – supervised learning models like XGBoost, Linear Regression, Feed-Forward Neural Networks, and time-series forecasting.
- Data visualization skills – Matplotlib, Seaborn, or similar tools.
- Experience working with real-world data pipelines and production deployment.
Bonus points
- Geospatial / Location Data (GIS, GeoPandas, PostGIS, Kepler.gl, etc.).
- Experience with real estate market data or economic/social trend analysis.
- MLOps knowledge – monitoring, versioning, and deploying ML models in production.
- Startup experience – working in a fast-moving, resource-constrained environment.
To apply
Send your CV, a snappy cover letter which highlights your expertise, skills and experience and any relevant links/attachments to your work.
Apply here
Have questions?Write to us