Operations Research Scientist – Logistics Optimization

About the role

The Operations Research Scientist (Logistics) will join Applied Materials' Global Services network optimization & transportation team in Bangalore. You will apply advanced analytics and optimization techniques to solve complex supply‑chain network problems, ranging from distribution design to routing and warehousing capacity.

Key responsibilities

• Develop and expand advanced supply‑chain analytics, creating proofs‑of‑concept and leading continuous‑improvement projects that reduce cost or increase service performance.
• Design and evaluate transportation network, hub‑spoke, and routing models using simulation and optimization software.
• Manage full‑lifecycle, cross‑functional programs that involve outsourced logistics providers, freight forwarders, and internal stakeholders.
• Define program objectives, analyze data, and drive quantifiable improvements while collaborating with IT to deploy solutions.
• Produce comprehensive output reports from optimization scenarios using Tableau or Power BI and support analytics initiatives across the network operations organization.
• Maintain multiple priorities under tight timelines and contribute thought leadership in supply‑chain optimization.

Required profile

• Graduate degree in Operations Research, Industrial Engineering, Supply Chain, Statistics or related quantitative field.
• 7‑10 years of experience in supply‑chain analytics, logistics or transportation.
• 5+ years of hands‑on data modeling using SQL and Python.
• 5+ years of experience with optimization software such as BY TMOD, Llamasoft, Gurobi, CPLEX or Xpress.
• Solid understanding of statistical modeling techniques (regression, classification, decision trees).
• Experience with machine‑learning algorithms (clustering, classification, reinforcement learning) and OR techniques (multi‑objective LP, MILP).

Required skills

• SQL
• Python
• Regression, classification, decision‑tree modeling
• BY TMOD, Llamasoft, Gurobi, CPLEX, Xpress
• Clustering, reinforcement learning
• Multi‑objective linear programming, MILP
• Tableau
• Power BI