Staff Data Scientist (TLM)

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.

All jobs

Staff Data Scientist (TLM)

Quince Careers, Bengaluru +1

The role

Staff Data Scientist – Supply Chain Operations Research

What you will do

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, technical decisions, and roadmaps clearly through written documentation and design discussions
Work effectively across distributed teams and time zones, ensuring technical decisions can be executed without requiring constant real-time guidance
Influence engineering and science architecture decisions related to optimization platforms, data pipelines, model serving, and evaluation infrastructure

Mentorship & Team Building

Mentor Data Scientists and Operations Research practitioners through technical guidance, code reviews, design discussions, and direct coaching
Raise the methodological and engineering bar across the OR team
Help define technical standards, best practices, and expectations for high-quality Operations Research
Contribute to hiring and help build a high-caliber Operations Research organization as the team scales

Business Partnership

Partner with supply chain, logistics, warehouse, and planning stakeholders to understand operational challenges and translate them into optimization problems
Convert complex model outputs into clear, actionable recommendations that business and operations teams can use
Educate stakeholders on model capabilities, limitations, assumptions, and appropriate use cases
Challenge over-fitted or incorrectly defined business problems and ensure scientific rigor is maintained in decision-making

Staff Data Scientist (TLM)

The role

Staff Data Scientist (TLM)

The role

What you will do

What you need

Nice to have

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Quince Careers