Data Scientist - Time Series Forecasting

Job Title : Data Scientist (Analytics)

Experience : 12+ Years (6+ years for Architects)

- Design and implement end-to-end machine learning pipelines for Time Series Forecasting.

- Apply statistical forecasting techniques such as ARIMA, Exponential Smoothing, and Prophet to real-world supply chain data.

- Develop and tune ML models using algorithms like XGBoost, LightGBM, etc., to enhance forecast accuracy.

- Collaborate with cross-functional teams to identify key demand drivers and optimize retail planning cycles.

- Translate business problems in demand planning into data science solutions using robust modeling techniques.

- Ensure seamless integration of ML models into business processes and the o9 platform.

- Communicate insights and recommendations clearly to non-technical stakeholders and leadership.

- Lead and mentor junior data scientists and data engineers in best practices and solutioning.

Required Skillsets :

- Strong background in Supply Chain, especially in Demand Planning and Retail Merchandise Financial Planning.

• Statistical models : ARIMA, Exponential Smoothing, Prophet
• Machine Learning models : XGBoost, LightGBM, etc.

- Proficient in Python and/or R, with strong command over data science libraries (e.g., pandas, NumPy, scikit-learn, statsmodels, prophet, etc.

- Experience in developing scalable, production-ready ML pipelines.

- Excellent communication, storytelling, and presentation skills to effectively convey insights to stakeholders.

- Strong cross-functional collaboration experience working with business, engineering, and product teams