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About the role
Job Description Data Scientist Time Series, Statistical Modelling & Azure Data Bricks Job Summary We are seeking a Data Scientist with strong expertise in Python, Statistical Modelling, Forecasting, and Machine Learning to develop advanced analytics solutions using Azure and Databricks. The ideal candidate will have hands-on experience in time-series forecasting, geospatial analytics, model interpretation, and large-scale data analysis to support data-driven decision making. Key Responsibilities Perform advanced data analysis, feature engineering, and exploratory analytics using Python. Develop, validate, and deploy predictive and machine learning models. Design and implement statistical forecasting and time-series models. Build geospatial analytics and location-based modelling solutions. Apply model explainability techniques and communicate insights to business stakeholders. Develop scalable analytical solutions using Databricks and Azure. Collaborate with business and technical teams to translate requirements into analytical solutions. Ensure data quality, governance, and validation throughout the model lifecycle. Contribute to reusable analytical frameworks, standards, and best practices. Required Skills Data Science & Analytics Statistical Modelling and Forecasting Time-Series Analysis Machine Learning Model Explainability & Interpretation Feature Engineering Hypothesis Testing and Predictive Analytics Programming Python SQL Libraries Pandas NumPy Scikit-learn Statsmodels Prophet Scipy Geospatial Analytics Experience with geospatial data analysis and modelling GeoPandas, Shapely or similar libraries (preferred) Cloud & Platform Databricks Azure Data & Analytics ecosystem Spark / PySpark Preferred Experience Energy / Utilities domain experience Forecasting, optimization, or operational analytics use cases Experience communicating analytical insights to business stakeholders Positive to Have Azure ML / MLOps SHAP, LIME, or similar Explainable AI .
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