Overview
Lead Data Scientist role focused on retail demand forecasting and related analytics/optimization using machine learning and statistical methods.
What you'll do
- Apply machine learning techniques including clustering, regression, ensemble learning, neural nets, time series, and optimizations.
- Develop and/or optimize models for demand sensing/forecasting, optimization, anomaly detection, and simulation/stochastic modeling.
- Use AI/ML advancements to solve business problems.
- Analyze complex problems, evaluate alternate methods, and articulate results with assumptions/reasons.
- Apply business metrics such as Forecast Accuracy, Bias, and MAPE and generate new ones as needed.
- Develop/optimize modules to call web services for real-time integration with external systems.
- Collaborate with clients and internal teams to ensure successful delivery of o9 projects.
What you'll need
- 6+ years of experience in time series forecasting at scale using heuristic-based hierarchical best-fit models.
- Experience with algorithms like exponential smoothing, ARIMA, prophet, and custom parameter tuning.
- Applied analytical experience in supply chain/planning areas such as demand planning, supply planning, and market intelligence.
- Statistical background.
- Bachelor’s degree in computer science, mathematics, statistics, economics, engineering, or related field.
- Programming in Python and/or R for data science.
- Deep knowledge of statistical and machine learning algorithms, scalable ML frameworks, feature engineering, tuning, and testing.
Nice to have
- Optional but preferred experience with SQL, databases, and ETL tools.
- Preferred experience with distributed data/computing tools such as Map/Reduce, Hadoop, Hive, Spark, or Gurobi.
- Preferable experience with deep learning frameworks such as Keras, Tensorflow, or PyTorch.
- Experience implementing planning applications is a plus.
- Understanding of supply chain concepts is preferable.
- Masters degree in related fields is preferred.
Details
Read the full description and apply on the company’s own careers page.
