• 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.
• Leverage alternative data sources (social trends, mobility data, economic indicators) to enhance predictive accuracy.
• 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.

What We’re Looking For

Core Skills & 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 Skills (Nice to Have)
• 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.