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. Must have at least 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.
Job ID: 151522655
Skills:
Machine Learning, Python, Sql, Statistical Analysis, Data Analysis, R, quantitative methods
Skills:
Time Series, Pyspark, Azure Databricks, Unsupervised Learning, Sql, Deep Learning, Nlp, Docker, Kubernetes, Python, supervised learning, ensemble methods, GenAI applications, CI CD pipelines, advanced algorithms
Skills:
Python, Sql, Statistical Analysis, R, program evaluation, data metrics analysis
Skills:
causal inference , Databricks, Python, Sql, DiD, Forecasting, DoubleML, R, Synthetic Control, AI-enabled solutions
Skills:
Github, Google Cloud Platform, Team Mentoring, Gcp, Bitbucket, Gitlab, Azure Cloud Services, Airflow, Customer Service Excellence, Ai, MLflow, Business Data Analysis, Written Communication, pair programming, requirements from stakeholders, Version Control Software