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Data Scientist III (Team- Valmo)

Meesho· Tech – Data Science
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Hybrid (Bangalore, Karnataka)Full Time EmployeePosted 1w ago

About the role

Data Scientist 3 (Operations Research) at Meesho’s Valmo (in-house logistics) focused on network design and end-to-end optimization for Valmo’s delivery network, mentoring juniors, and driving measurable workload through production-ready optimization systems.

Responsibilities

  • Own a workstream end to end: decide which problems are worth solving, set and drive its roadmap, and be accountable for the movement of its metrics.
  • Formulate complex, loosely defined business problems in network design, routing, scheduling, allocation and capacity planning as LP, MILP, MINLP or constraint programming models, with explicit assumptions.
  • Solve them at scale with decomposition (Benders, Lagrangian relaxation, column generation, branch-and-price), heuristics and metaheuristics (large neighbourhood search, ALNS, tabu search) and constraint programming, within real planning-time budgets.
  • Handle uncertainty with stochastic, robust and chance-constrained optimisation, and test decisions through simulation before they reach the ground.
  • Combine OR with ML and DL, such as demand and volume forecasting, ETA prediction and learned heuristics, wherever it improves the decision.
  • Write production-grade code and work with engineering to ship solvers and models into systems that run every day, with testing, monitoring and reproducible pipelines.
  • Mentor DS1s and DS2s on formulation, modelling craft and code quality; align the roadmap with product, engineering, operations and business; and explain trade-offs to senior leaders in decision terms.
  • Publish your work at A* conferences and journals, as part of a team with a highly innovative work culture.

Qualifications

  • Bachelor's, Master's or PhD in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Computer Science or a related quantitative field.
  • 5–8 years of experience (or 3+ years with a PhD) applying operations research to real-world problems, with optimisation models deployed in production.
  • Deep expertise in mathematical optimisation (LP, MILP, network flows, integer and combinatorial optimisation), with a proven ability to formulate ambiguous problems, design heuristics, and break complex problems into simpler sub-problems.
  • Experience with large-scale solution methods (decomposition, column generation, heuristics and metaheuristics, constraint programming) and with optimisation under uncertainty and simulation.
  • Hands-on experience with solvers and modelling tools such as Gurobi, CPLEX, OR-Tools (including CP-SAT), HiGHS, Pyomo or PuLP.
  • Strong programming: expert Python and SQL, PySpark or similar for large datasets, and solid software engineering (object-oriented design, Git, testing, code review). Fluency with AI coding agents, with the judgement to check their output.
  • Working knowledge of ML and DL (forecasting, regression, tree-based models, neural networks) and of how to combine them with optimisation.
  • Experience leading a workstream and mentoring junior data scientists, and the ability to explain trade-offs and limitations to senior business and operations leaders.

Skills

Required:Operations ResearchOptimization MethodsProgramming
Nice to have:ML/DL integration
Last updated Oct 21, 2026. Interested? Apply on the company site.
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