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Company: Datacrew.ai
Location: Chennai (Onsite)
Datacrew.ai is seeking a skilled Data Scientist (Demand Forecasting) to join our growing analytics team. In this role, you will design, deploy, and optimize demand prediction models across industries such as food and retail. By leveraging machine learning, time series analysis, and external domain factors, you will deliver actionable insights that drive smarter business decisions.
Develop and enhance forecasting models using time series, statistical, and ML techniques for SKU- and branch-level demand prediction.
Partner with stakeholders to define requirements and identify relevant data sources (historical sales, calendar, promotions, external datasets).
Perform feature engineering to integrate seasonality, holidays, promotions, weather, and external drivers into models.
Conduct thorough data preprocessing, validation, and analysis to ensure robust and reliable forecasts.
Collaborate with data engineering and business teams to deploy models into production and automate recurring forecasts.
Track and evaluate model performance using MAE, RMSE, MAPE, and refine models based on results.
Prepare documentation, dashboards, and presentations for technical and business audiences.
Stay current on advances in time series forecasting, ML, and demand analytics.
Bachelor’s/Master’s in Data Science, Statistics, Computer Science, Operations Research, or related field.
4–5 years’ experience in forecasting/analytics (retail, QSR, FMCG, or manufacturing preferred).
Hands-on expertise in:
Time series models: ARIMA/SARIMA, Exponential Smoothing, Prophet
Machine learning models: XGBoost, LightGBM, Random Forest, Neural Networks for time series
Proficiency in Python (pandas, scikit-learn, statsmodels, Prophet, etc.); SQL is a plus.
Experience in feature engineering with holiday/event calendars and external data.
Familiarity with visualization tools (Tableau, Power BI, matplotlib, seaborn).
Strong problem-solving, detail orientation, and business translation skills.
Excellent communication and collaboration abilities.
Experience deploying forecasting models in production/cloud environments.
Knowledge of retail/restaurant analytics at SKU and store/branch level.
Exposure to big data tools, cloud platforms (AWS, GCP, Azure), and workflow automation.
Experience with deep learning models for time series (LSTM, GRU).
