Job Description: Data Scientist – Demand Forecasting Company: Datacrew.ai Location: India (Onsite) Date: July 22, 2025 Overview Datacrew.ai is seeking a Data Scientist with expertise in demand forecasting to join our growing analytics team. This role will focus on building, deploying, and optimizing demand prediction models for diverse industries including food and retail. You will leverage machine learning, statistical modeling, and domain-specific external factors to deliver actionable business insights. Key Responsibilities • Develop, implement, and improve forecasting models using time series, statistical, and machine learning techniques for granular (SKU/branch-level) and aggregate demand prediction. • Work with business stakeholders to understand requirements and identify relevant data sources (historical sales, external, and calendar data). • Perform feature engineering to integrate variables such as seasonality, holidays, promotions, weather, and other external factors into forecasting models. • Conduct data analysis, preprocessing, and validation to ensure high model accuracy and reliability. • Collaborate with data engineering and business teams to deploy models into production environments and automate recurring forecasts. • Evaluate model performance using metrics such as MAE, RMSE, and MAPE; iterate based on results and feedback. • Prepare clear documentation, dashboards, and presentations on model outcomes and recommendations for both technical and non-technical audiences. • Stay updated on latest advances in demand forecasting, time series analytics, and relevant technologies. Required Skills & Experience • Bachelor’s or Master’s in Data Science, Statistics, Computer Science, Operations Research, or a related field. • 4-5 years’ experience in a data scientist or forecasting/analytics role (retail, QSR, FMCG, manufacturing, or similar preferred). • Strong practical experience with: • Time series forecasting (e.g., ARIMA/SARIMA, Exponential Smoothing, Prophet) • Machine Learning models (e.g., XGBoost/LightGBM, Random Forest, neural networks for time series) • Proficiency in Python (pandas, scikit-learn, statsmodels, Prophet, etc.); SQL experience a plus. • Experience with feature engineering for forecasting models, including holiday/event calendars and external datasets. • Familiarity with data visualization and dashboarding tools (e.g., Tableau, PowerBI, matplotlib, seaborn). • Strong problem-solving skills, attention to detail, and ability to translate business needs into analytical solutions. • Effective communication and collaboration skills. Preferred • Experience deploying forecasting solutions into production/cloud environments. • Understanding of retail or restaurant analytics at product/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 (e.g., LSTM, GRU).