Staff Data Scientist (TLM)

About this job

Quince is a direct-to-consumer brand focused on providing high-quality essentials at low, sustainable prices through an innovative manufacturer-to-consumer model. The company utilizes proprietary technology, analytics, and data to scale operations across apparel, accessories, and home goods. As a Staff Data Scientist (TLM) for Supply Chain Operations Research based in Bengaluru, you will join the Supply Chain Planning Science team as a founding science leader for the India-based OR team. In this role, you will lead the development and productionization of advanced Operations Research solutions that drive crucial supply chain decisions. A normal day involves owning OR workstreams end-to-end, translating complex operational challenges into optimization models, partnering with engineering and logistics teams across geographies, establishing scientific standards, and mentoring data scientists to build scalable, AI-native optimization systems.

Responsibilities

• Own Operations Research workstreams end-to-end across warehouse routing, shipping costs, transportation, network flow, and inventory planning.
• Translate complex supply chain challenges into well-defined optimization problems using LP, MIP, CP, and metaheuristics.
• Develop, productionize, and continuously improve optimization models based on real-world operational feedback.
• Establish high methodological standards and data-driven experimentation frameworks for the organization.
• Drive the adoption of AI-native workflows, including LLM-assisted model formulation and agentic problem decomposition.
• Set the technical and scientific direction for the India-based Operations Research team in collaboration with global partners.
• Mentor data scientists through technical guidance, code reviews, design discussions, and direct coaching.

Requirements

• Experience leading and owning Operations Research workstreams end-to-end.
• Expertise in optimization methodologies such as Linear Programming, Mixed-Integer Programming, and stochastic optimization.
• Ability to work effectively with sparse, noisy, incomplete, and non-stationary operational data.
• Track record of developing and productionizing optimization models for real-world operational impact.
• Experience collaborating across distributed teams and global geographies.
• Strong background in technical leadership, mentorship, and raising engineering and scientific standards.

Good to have

• Experience with AI-native workflows and LLM-assisted model formulation.
• Familiarity with warehouse routing and multi-modal transportation optimization.

Who should apply

This role suits an experienced data scientist and technical leader with a strong background in supply chain operations research and production-grade optimization systems. It is ideal for professionals who enjoy building systems from scratch, setting scientific standards, and mentoring teams in a fast-paced environment. The posting does not mention fresher eligibility, so applicants should possess relevant industry experience in operations research and supply chain analytics.

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