Data Scientist

Job Role: Data ScientistJob Location: RemoteAbout 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.