DATA SCIENTIST - DATA SCIENTIST

Job Description

We are looking for a highly skilled Data Scientist / Machine Learning Engineer with strong expertise in Python-based development, demand forecasting, and Azure analytics platforms. The candidate will be responsible for designing, developing, and deploying scalable forecasting and machine learning solutions, working closely with business and engineering teams to drive data-driven decision-making.

Key Responsibilities

• Design, develop, and maintain Python-based data science and machine learning solutions using industry-standard practices.
• Implement and optimize demand forecasting models, including but not limited to statistical and ML-based forecasting techniques
• Develop and maintain unit tests using unittest / pytest to ensure code quality, reliability, and maintainability.
• Build, manage, and optimize data pipelines using Azure Databricks.
• Work with Azure SQL for data ingestion, transformation, and analytical queries.
• Collaborate using Git/GitHub, following best practices for version control, code reviews, and CI/CD.
• Apply Machine Learning techniques to solve business problems, including feature engineering, model evaluation, and performance tuning.
• Support AML (Azure Machine Learning) for model experimentation, training, and deployment where applicable.
• Partner with business stakeholders to translate demand planning and forecasting requirements into technical solutions.
• Monitor, retrain, and optimize models in production to ensure accuracy and business relevance.
• Document solution designs, assumptions, and model behavior for transparency and maintainability.

Required Skills & Experience

Technical Skills

• Strong proficiency in Python for data science and ML development.
• Hands-on experience with unit testing frameworks (unittest, pytest).
• Solid experience with demand forecasting algorithms, including ARIMA, SARIMA, Prophet, and regression-based models.
• Practical experience with Azure Databricks and Azure SQL.
• Experience working with Azure Machine Learning (AML) environments.
• Strong understanding of Git/GitHub and collaborative development workflows.

Data & ML Skills

• Experience in time-series analysis and forecasting /pricing
• Knowledge of feature engineering, model validation, and performance metrics.
• Understanding of ML lifecycle management and production considerations.