Applied Scientist, Selection And Inventory Science

Job description

As an Applied Scientist, you will work on high-impact, real-world problems in product selection and inventory management using techniques from operations research, causal inference, forecasting, reinforcement learning and agentic artificial intelligence. You will develop state-of-the-art solutions to optimize customer experience with supply chain levers. You will partner closely with engineering and business teams to turn these models into trusted, scalable decisions.

You will publish your work in top conferences and journals.

Key job responsibilities

- Develop stochastic and multi-objective optimization models for assortment planning.

- Apply causal inference and forecasting to measure impact and inform decisions.

- Build reinforcement learning foundation models for large-scale sequential decision making in inventory management.

- Translate rigorous science into clear, actionable recommendations, and communicate them to stakeholders.