Demand Forecasting Data Scientist

Location: Vasanthanagar

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:
Num Py, Pandas, Sci Py
scikit-learn
stats models
Tensor Flow / 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.