Job Title: Demand Forecasting Data Scientist
Experience: 6+ Years
Location: Bangalore
Job Summary
We are seeking an experienced Demand Forecasting Data Scientist with strong expertise in time series forecasting, machine learning, and supply chain analytics . The ideal candidate will have hands-on experience working with Databricks and Python , a deep understanding of demand planning use cases, and the ability to deliver scalable, production-ready forecasting solutions. This role requires a sharp analytical mindset, fast learning ability, and strong collaboration skills.
Key Responsibilities
- Design, develop, and deploy demand forecasting models using time series, machine learning, and deep learning techniques.
- Build end-to-end forecasting pipelines on Databricks leveraging distributed computing and scalable architectures.
- Apply statistical and ML techniques such as ARIMA/SARIMA, Prophet, XGBoost, Random Forest, LSTM, GRU , TimeGPT and hybrid models.
- Collaborate closely with supply chain, demand planning, and business stakeholders to translate business problems into analytical solutions and should be a able to full ownership.
- Perform feature engineering using internal and external drivers (promotions, seasonality, holidays, weather, etc.).
- Evaluate and improve forecast accuracy using appropriate metrics (MAPE, wMAPE, Bias).
- Optimize models for performance, scalability, and interpretability in production environments.
- Conduct exploratory data analysis and present actionable insights to both technical and non-technical audiences.
- Contribute to best practices in coding, model governance, documentation, and MLOps workflows.
- Mentor junior team members and actively participate as a strong team player in cross-functional initiatives.
Required Skills & Qualifications
Technical Skills
- 6 years of experience as a Data Scientist with a strong focus on demand forecasting or supply chain analytics .
- Strong hands-on experience with Python and its associated libraries:
- NumPy, Pandas, SciPy
- scikit-learn
- statsmodels
- TensorFlow / PyTorch (for DL models)
- Solid experience with Time Series Forecasting techniques and real-world demand planning use cases.
- Hands-on experience with Databricks , including Spark, notebooks, and distributed data processing.
- Practical exposure to Machine Learning and Deep Learning model development and deployment.
- Experience working with large, complex datasets in cloud-based or big data environments.
- Practical understanding of Nixtla library is a plus.
- Experience with MLOps , model monitoring, and CI/CD pipelines.
Domain Knowledge
- Strong Supply Chain domain knowledge , especially demand forecasting, inventory planning, and sales forecasting.
- Understanding of forecast lifecycle, demand variability, and business constraints.
Soft Skills & Competencies
- Sharp analytical mindset with strong problem-solving skills.
- Ability to pick up new concepts and tools quickly in a fast-paced environment.
- Strong communication skills with the ability to explain complex models in simple terms.
- Highly collaborative with a strong team-player attitude .
- Proactive, self-driven, and ownership-oriented approach to work.
Preferred (Good to Have)
- Exposure to cloud platforms (Azure / AWS / GCP).
- Experience working in Agile or cross-functional delivery teams.
- Prior experience in retail, CPG, manufacturing, or e-commerce domains.