Data Scientist

Experience:

• The ideal candidate has at least 3–5 years of hands-on experience in data science or a related field, with a demonstrable track record of delivering machine learning solutions in production.
• Prior experience working with geospatial data and tools is strongly preferred, as is experience in domains involving demographic modelling.

Skills:

• The candidate 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.
• The candidate should be familiar with the full ML lifecycle, from data wrangling and feature engineering through to model evaluation, deployment, and monitoring.
• Candidate should be comfortable with more advanced ML techniques such as ensemble learning, regularisation, agent-based modelling, forecasting, etc.
• Beyond technical skills, the role requires strong communication skills to present findings and recommendations clearly to non-technical stakeholders, and the ability to work collaboratively in a cross-functional team environment. 

By proceeding with the job application, you are deemed to have read and acknowledged our Job Applicant Privacy Policy and consented to us using the personal data you shared for the purpose stated in the said policy.