Data Scientist
Summary
Designs and deploys machine learning models using Python, cloud platforms, and geospatial tools to solve problems in urban planning or public-sector analytics.
· Must have at least 4–7 years of hands-on experience in data science or a related field, with a demonstrable track record of delivering machine learning solutions in production.
· Should be proficient in Python and relevant data science libraries such as scikit-learn, PyTorch, or TensorFlow.
· Knowledge of geospatial tools and frameworks such as GeoPandas, QGIS, PostGIS, or ArcGIS is a bonus.
· Strong skills in SQL and experience with cloud data platforms (e.g. AWS, GCP, or Azure) are expected.
· Must be familiar with the full ML lifecycle, from data wrangling and feature engineering through to model evaluation, deployment, and monitoring.
· Must be comfortable with more advanced ML techniques such as ensemble learning, regularization, agent-based modelling, forecasting, etc.
· Prior experience working with geospatial data and tools is strongly preferred, as is experience in domains involving demographic modeling, urban planning, or public sector analytics.