Data Scientist

Job Role: Data Scientist

Job Location: Remote

About the Role:

We are seeking an experienced Data Scientist / Machine Learning Engineer to lead a Proof of Concept (PoC)initiative for migrating our existing on-premise Demand Forecasting (DF) algorithm, currently implemented in Python, to a cloud-based Azure Machine Learning (Azure ML) environment. The ideal candidate will have deep expertise in forecasting models, hands-on experience with Python, and proven capability in leveraging Azure ML for model deployment and scaling.

Key Responsibilities:

• Lead the PoC initiative to transition the current on-premise Python-based demand forecasting model to an Azure ML–based cloud solution.
• Evaluate existing forecasting methodologies, optimize algorithms, and ensure seamless integration within Azure ML pipelines.
• Design, build, and deploy forecasting models that ensure scalability, maintainability, and performance efficiency in the cloud.

Required Skills & Qualifications:

• 8–12 years of experience in Data Science, with a strong focus on Demand Forecasting or Time Series Modeling.
• Advanced proficiency in Python, including libraries such as pandas, NumPy, scikit-learn, statsmodels, and Prophet (or equivalent).
• Hands-on experience with Azure ML — including workspace management, pipelines, model training/deployment, and MLOps integration.
• Solid understanding of forecasting techniques, model evaluation metrics, and optimization approaches.
• Experience in migrating ML models from on-premise to cloud platforms (preferably Azure).
• Familiarity with version control (Git), CI/CD for ML (MLflow, Azure DevOps), and containerization (Docker) is desirable.