Data Scientist

. 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.