Staff Data Scientist

About the role

You will own the end-to-end lifecycle of operations research and data science solutions for supply chain planning at Quince. You will formulate complex warehouse routing, transportation, and network design problems and translate them into scalable, production-ready algorithms. You will partner closely with logistics operators and planners to turn ambiguous business needs into testable analytical hypotheses and measurable impact. You will lead the design and experimentation of optimization models, simulation frameworks, and decision engines that directly influence service levels and cost efficiency. You will establish rigorous evaluation methodologies to quantify the operational and financial value of your models in live environments. You will mentor junior data scientists and collaborate with engineering to ensure robust, maintainable, and well-documented implementations. You will translate high-level business objectives into mathematical formulations and prioritize trade-offs between accuracy, runtime, and practicality. You will act as the primary technical interface between the supply chain team and the technology organization.

Key facts

What you'll do

Develop and deploy operations research models that optimize warehouse routing, transportation, and network planning across Quince's fulfillment ecosystem.

Design and implement optimization and simulation algorithms that balance service level, cost, and capacity constraints in dynamic, real-world conditions.

Collaborate with supply chain planners and logistics partners to translate business requirements into quantifiable objectives and constraints for OR models.

Lead the productionization of data science and operations research workflows, ensuring solutions are scalable, maintainable, and performant in production environments.

Own the development of purchase order allocation and inventory planning models that improve throughput and reduce waste across the supply chain.

Define key performance indicators and experimental frameworks to evaluate the impact of optimization and decision-support tools on operational and financial outcomes.

Partner with data engineering teams to build reliable data pipelines, feature stores, and model infrastructure that support advanced analytics and optimization workloads.

Drive experimentation and continuous improvement by testing alternative methodologies, benchmarking results, and refining models based on observed performance.

Act as a technical leader in the design of routing, scheduling, and network optimization tools that integrate directly with planning and execution systems.

Communicate insights and model behavior clearly to both technical and non-technical stakeholders, ensuring trust, transparency, and alignment on decision logic.

Champion best practices in model documentation, versioning, and reproducibility to enable long-term maintainability and cross-team collaboration.

Identify opportunities to leverage stochastic modeling, combinatorial optimization, and machine learning techniques to address evolving supply chain challenges.

Requirements

Demonstrate a strong background in operations research, data science, or a related quantitative field with proven experience in optimization and modeling.

Bring experience in solving large-scale, real-world problems involving routing, scheduling, allocation, or network design using analytical and data-driven methods.

Showcase a track record of turning business problems into mathematical formulations and implementing solutions that drive measurable operational improvements.

Have hands-on experience with programming languages, libraries, and tools commonly used in data science and optimization work.

Exhibit strong analytical rigor, structured thinking, and the ability to decompose complex problems into manageable components.

Demonstrate excellent communication skills and the ability to work effectively with cross-functional partners, including planners, engineers, and operations teams.

Commit to working in a fast-paced, rapidly scaling environment where priorities evolve and problem-solving requires both independence and collaboration.

Nice to have

Experience with supply chain, logistics, or retail contexts where optimization directly impacts cost and service metrics.

Familiarity with modern data stack integration, including pipelines, feature stores, and model deployment patterns.

Background in stochastic modeling, simulation, or combinatorial optimization methods.

Experience leading technical projects in cross-functional settings and mentoring other analysts or data scientists.

Practical notes

This role is based in Bengaluru and requires reliable local connectivity.

Applicants must be eligible to work in India without sponsorship for this position.

The engagement terms and specific working hours should be confirmed directly with the source.

Travel requirements, if any, and visa-related considerations should be verified with the official job details.

Deadlines for submission and interview stages must be confirmed through the original job source.