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Staff Data Scientist (TLM)

Quince· Logistics Engineering
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Hybrid (Bengaluru)Full-timePosted 2mo ago

About the role

Staff Data Scientist – Supply Chain Operations Research to join the Bangalore team, leading development and productionization of advanced OR solutions for warehouse routing, transportation, network planning, inventory, and PO allocation; owns OR workstreams end-to-end and mentors the team.

Responsibilities

  • 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 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
  • Establish and maintain high methodological standards for Operations Research across the organization
  • Evaluate different optimization approaches using rigorous, data-driven experimentation
  • 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
  • Drive the adoption of AI-native workflows across Operations Research including LLM-assisted model formulation and AI-assisted experiment design
  • Identify opportunities where AI can accelerate scientific workflows while maintaining rigorous validation
  • 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
  • Set the technical and scientific direction for the India-based OR team
  • Partner with Palo Alto teams to establish a cohesive science roadmap across geographies
  • Communicate complex methodologies and roadmaps clearly through documentation and discussions
  • Work effectively across distributed teams and time zones
  • Influence engineering and science architecture decisions related to optimization platforms, data pipelines, model serving, and evaluation infrastructure
  • Mentor Data Scientists and Operations Researchers through technical guidance, code reviews, and coaching
  • Raise the methodological and engineering bar across the OR team
  • Help define technical standards and best practices for high-quality OR work
  • Contribute to hiring and build a high-caliber OR organization as the team scales
  • Partner with supply chain, logistics, warehouse, and planning stakeholders to translate challenges into optimization problems
  • Convert model outputs into actionable recommendations for business and operations teams
  • Educate stakeholders on model capabilities, limitations, and appropriate use cases
  • Challenge over-fitted or poorly defined problems and maintain scientific rigor in decision-making

Qualifications

  • 9–12 years of experience in Operations Research, Data Science, Applied Mathematics, Industrial Engineering, or related quantitative discipline
  • Deep expertise in optimization methodologies including LP, MIP, Constraint Programming, Vehicle Routing, Network Flow, Metaheuristics, and Stochastic Optimization
  • Demonstrated experience owning OR or optimization workstreams end-to-end, from problem formulation through production deployment and measurable business impact
  • Strong understanding of supply chain optimization problems such as warehouse operations, transportation, inventory, network planning, logistics, or procurement
  • Strong engineering capabilities to productionize analytical/optimization solutions, including feature pipelines, solver integration, model serving, and experimentation infrastructure
  • Experience with real-world operational datasets that may be large, noisy, sparse, or non-stationary
  • Strong understanding of experimentation, backtesting, model evaluation, and scientific validation
  • Experience partnering with engineering teams to build and deploy production-grade data science/optimization systems
  • Demonstrated experience mentoring Data Scientists, Operations Researchers, or other technical professionals
  • Strong written and verbal communication skills with ability to influence stakeholders
  • Ability to operate in ambiguous, fast-paced environments and independently drive complex problems
  • Experience using AI/LLM tools to accelerate scientific workflows with rigorous validation
  • Advanced degree in Operations Research, Industrial Engineering, CS, Statistics, Applied Mathematics, or related field preferred

Skills

Required:Operations ResearchOptimization MethodologiesProductionizing ModelsExperimentation & ValidationCommunication & Collaboration
Nice to have:AI-Native Workflows

Benefits

  • Not specified in the description
Last updated Sep 2, 2026. Interested? Apply on the company site.
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