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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:
Hadoop, Data Warehousing, Sql, Mapreduce, Tensorflow, Pytorch, Python, data analysis tools, scikit-learn, Hugging Face Transformers, Flink, large-scale ML models, ETL processes, ML pipeline orchestration platforms
Skills:
Shell, Tableau, Python, Sql, R, Looker, Risk management, Modeling, Analytics
Skills:
Predictive Modelling, Sql, Python, graph analytics, experimentation frameworks, anomaly detection
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
Skills:
causal inference , Clustering, Sql, Python, Uplift modelling, Time-series, Demand Forecasting, Instrumental variables, Difference-in-differences, Regression, Synthetic control, Classification, Price-elasticity estimation, Experiment design, Statistical ML modelling