Data Scientist – Demand Forecasting

Company Overview

D atacrew.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.

Job Summary

The Data Scientist in this role will leverage machine learning, statistical modeling, and domain-specific external factors to deliver actionable business insights, aiming to enhance overall operational efficiency and accuracy in demand forecasting.

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 Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (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.

Qualifications

• 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, Quick Service Restaurant (QSR), Fast-Moving Consumer Goods (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 (including libraries such as pandas, scikit-learn, statsmodels, Prophet, etc.); SQL experience is 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, Power BI, matplotlib, seaborn).
• Strong problem-solving skills, attention to detail, and ability to translate business needs into analytical solutions.
• Effective communication and collaboration skills.

Preferred Skills

• 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).

Experience

4 - 5 years' experience in a data scientist or forecasting/analytics role related to retail or similar industries is preferred.

Environment

The position is based in India, and it requires onsite presence.

Salary

Salary information is not specified.

Growth Opportunities

Potential career advancement opportunities may arise within the analytics team and across the organization as business needs evolve.

Benefits

Benefits information is not specified.