LEAD DATA SCIENTIST - Project forecasting

Job Description

We are looking for a highly skilled Forecasting Data Scientist with strong expertise in Python-based development, time-series forecasting, and applied statistical and machine learning techniques. The candidate will be responsible for designing, developing, and deploying scalable forecasting solutions to support business planning and decision-making across domains such as demand planning, pricing, supply chain, and revenue forecasting, working closely with business, analytics, and engineering teams.

Key Responsibilities

? Design, develop, and maintain Python-based forecasting and data science solutions using industry best practices.

? Develop and implement time-series forecasting models using statistical and machine learning techniques.

? Apply forecasting approaches such as ARIMA, SARIMA, Prophet, and regression-based models.

? Perform EDA, data preprocessing, and feature engineering for time-series and external drivers.

? Build scalable forecasting pipelines across multiple hierarchies and granularities.

? Measure, monitor, and improve forecast accuracy using appropriate evaluation metrics.

? Deploy forecasting models into production environments and support downstream integrations.

? Collaborate with business stakeholders to convert planning requirements into technical solutions.

? Document assumptions, methodologies, and forecast outputs clearly.

Required Skills & Experience

Technical Skills

? Strong proficiency in Python for forecasting and data science development.

? Hands-on experience with statsmodels, Prophet, scikit-learn, or similar libraries.

? Strong understanding of classical and ML-based forecasting techniques.

? Experience with SQL for data extraction and analytical queries.

? Experience building batch or automated forecasting pipelines.

? Exposure to cloud platforms such as AWS, Azure, or GCP.

? Experience using Git/GitHub for version control and collaboration.

Data & Forecasting Skills

? Strong experience in time-series analysis, trend and seasonality modeling.

? Experience incorporating promotions, pricing, holidays, and external regressors.

? Understanding of forecast accuracy metrics, back-testing, and validation techniques.

? Experience with forecast lifecycle management, monitoring, and re-training.

? Ability to clearly communicate forecast assumptions and insights to stakeholders.

Experience & Education

? 6?8 years of experience in forecasting, data science, or applied analytics roles.

? Bachelor?s or Master?s degree in Statistics, Mathematics, Economics, Computer Science, or Data Science.

? Experience mentoring junior analysts or data scientists is a plus.