Data Scientist – Demand Forecasting

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About the Role

Data Scientist – Demand Forecasting

You will collaborate closely with cross-functional teams, applying your expertise in machine learning and statistical modeling to optimize forecasting accuracy and business efficiency. The ideal candidate is curious, analytical, and a strong communicator who thrives on translating complex data into actionable insights.

Key Responsibilities

• Develop and enhance demand forecasting models using machine learning and statistical techniques.
• Work closely with engineering, supply chain, and business stakeholders to deliver data-driven forecasting solutions.
• Conduct feature engineering, hyperparameter tuning, and rigorous model evaluation.
• Use Python and SQL to build and maintain reproducible, scalable code for data analysis and model deployment.
• Run experiments to test forecasting improvements and validate model performance with historical and real-time data.
• Translate technical concepts and model behavior into clear, actionable insights for non-technical stakeholders.
• Support deployment of algorithms into production systems and build data pipelines for automation.
• Continuously explore new data sources and methodologies to improve forecast accuracy.
• Communicate findings and recommendations through dashboards, presentations, and reports.
• Travel up to 20% internationally, if required.

Required Qualifications

• Master’s degree in a quantitative field (e.g., Data Science, Statistics, Mathematics, Physics, Computer Science, or Engineering).
• 4–7 years of hands-on experience in data science, analytics, or a similar analytical role.
• Proficiency in Python (Pandas, NumPy, Scikit-learn, etc.) and SQL; experience with big data tools (e.g., Hadoop, Hive, Spark, or Scala) is a plus.
• Strong grasp of time-series forecasting techniques and statistical modeling.
• Solid skills in feature engineering, model evaluation, and hyperparameter optimization.
• Experience building production-ready, maintainable, and tested code.
• Ability to clearly communicate data assumptions, modeling approaches, and findings to both technical and non-technical stakeholders.
• Knowledge of data pipelines and integrating ML models into production systems.
• Collaborative mindset with strong problem-solving skills and the ability to work independently.

Preferred Qualifications

• Experience in supply chain or logistics-related forecasting.
• Strong communication and stakeholder management skills.
• Familiarity with data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly, Power BI, Tableau).
• Knowledge of Microsoft Azure cloud platform.
• Experience designing and building APIs for model integration.

Why Join Us?

• Work on impactful, real-world business challenges.
• Join a collaborative and forward-thinking team.
• Enjoy flexibility with remote working options.
• Engage in continuous learning and cross-domain exposure.