Staff Data Scientist (TLM)

About this role

ABOUT QUINCE

Founded in 2018, Quince was built to challenge the idea that nice things have to cost a lot. Our mission is simple: to make really high quality essentials for really low prices, produced fairly and sustainably. We believe everyone deserves exceptional craftsmanship and timeless design without the traditional markups. Quince is a direct-to-consumer (DTC) model that cuts out middlemen and leverages just-in-time manufacturing to minimize waste and maximize value.

Quince is a tech company disrupting the retail industry by putting AI, analytics and automation at the center of everything we do. Our unwavering commitment to excellence and company values guide our teams and actions:

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Customer First: We prioritize customer satisfaction in every decision.

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High Quality: True quality means premium materials and rigorous production standards you can feel good about.

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Essential Design: We focus on timeless, functional essentials instead of chasing trends.

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Always a Better Deal: Innovation and transparency ensure value for both customers and partners.

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Social & Environmental Responsibility: We commit to sustainable materials, ethical production, and fair wages.

Quince partners with world-class manufacturers across the globe and serves millions of customers. With strong investor backing and a focus on sustainable growth, we are a company that is rapidly scaling while maintaining a commitment to quality, simplicity, and radical price transparency.

OUR TEAM AND SUCCESS

At Quince, you will be part of a high-performing team that is redefining what quality, value, and sustainability mean in modern retail. We are a destination for builders, innovators, and operators to come together and challenge the status quo. Our collective ambition is bold. We are creating an entirely new category and customer experience – one that democratizes luxury and provides high quality products at radically low prices. That mission demands a world-class team committed to excellence.

If you are motivated by impact, growth, and purpose, you will find a strong sense of belonging at Quince.

THE ROLE

Staff Data Scientist – Supply Chain Operations Research

We are seeking a Staff Data Scientist : Supply Chain Operations Research to join our Supply Chain Planning Science team in Bangalore. In this role, you will lead the development and productionization of advanced Operations Research solutions that power critical supply chain decisions across warehouse routing, transportation, network planning, inventory, and purchase order allocation.

As a founding science leader for the India-based Operations Research team, you will own OR workstreams end-to-end — from problem formulation and methodology selection to production deployment, experimentation, and measurable business impact. You will partner closely with Supply Chain Planning, Engineering, Logistics, Warehouse Operations, and Science teams across Bangalore and Palo Alto to translate complex operational problems into scalable optimization solutions.

Success in this role means building production-grade optimization systems that materially improve supply chain efficiency, establishing strong scientific standards for the OR organization, and raising the technical bar through mentorship, collaboration, and AI-native approaches to Operations Research.

Responsibilities:

Operations Research & Workstream Ownership

• Own Operations Research workstreams end-to-end across areas such as dynamic warehouse routing, shipping cost optimization, multi-modal transportation, network flow, inventory planning, and PO allocation

• Translate complex supply chain and operational challenges into well-defined optimization problems and measurable objectives

• Select and apply appropriate optimization methodologies including Linear Programming (LP), Mixed-Integer Programming (MIP), Constraint Programming (CP), vehicle routing, network flow, metaheuristics, and stochastic optimization

• Develop, productionize, and continuously improve optimization models based on real-world operational feedback and measurable business outcomes

• Partner with Planning Tools and Engineering teams to define requirements for solver integration, feature pipelines, model serving, evaluation infrastructure, and production systems

Methodology & Scientific Rigor

• Establish and maintain high methodological standards for Operations Research across the organization

• Evaluate different optimization approaches using rigorous, data-driven experimentation rather than relying on a single modeling methodology

• Define experimentation standards including clean data splits, historical backtesting, model validation, and robust evaluation frameworks

• Work effectively with sparse, noisy, incomplete, and non-stationary operational data

• Challenge assumptions, validate hypotheses rigorously, and be willing to reject approaches that do not demonstrate measurable impact

• Ensure optimization models are explainable, maintainable, and appropriate for real-world operational decision-making

AI-Native Science & Innovation

• Drive the adoption of AI-native workflows across Operations Research, including LLM-assisted model formulation, agentic problem decomposition, and AI-assisted experiment design

• Identify opportunities where AI can accelerate scientific workflows while maintaining rigorous validation and methodological standards

• Build and improve AI-augmented experimentation and optimization workflows

• Establish practical standards for evaluating AI-generated hypotheses, formulations, and recommendations before they influence production decisions

Technical Leadership & Cross-Geography Collaboration

• Set the technical and scientific direction for the India-based Operations Research team

• Partner closely with the Palo Alto Staff Data Scientist and Director, Supply Chain Planning Science & Platform to establish a cohesive science roadmap across geographies

• Communicate complex methodologies,…