I am an operations research practitioner with 6+ years of industry experience and 5 years of academic research experience. At Swiggy, as part of the core-logistics team, I have been primarily working on developing low latency and scalable solutions for the hyperlocal logistics optimisation problems for both food and groceries. Before joining Swiggy, I was a Data Science consultant at Antuit.ai where I worked with clients from logistics and agriculture industry. I have received my Masters and Ph.D. in Operations Research from the Department of Industrial Engineering and Operations Research, Indian Institute of Technology Bombay. My academic research work was focused in the core operations research areas like supply chain management, optimization, simulation. My industry experience ranges between various areas of data science (e.g. recommendation, classification, regression, demand forecasting, etc.) and operations research (e.g. first-mile, last-mile delivery optimization, inventory planning, vehicle routing, assignment problem, multi-objective optimization etc.). My areas of expertise include mathematical optimization (e.g. linear/non-linear/mixed-integer programming/simulation-based), simulation modelling (system dynamics, discrete-event, and Monte Carlo), supply chain management (e.g. inventory management, network design, demand forecasting), and machine learning (regression, classification, clustering, feature engineering). Technical Skills: Programming Languages: Python, R, C, C++ Optimization Solvers: OR-Tools, CPLEX, GUROBI, GLPK, Excel Solver Optimization Programming Languages: AMPL, Python-Pyomo, Python-PuLP, ILOG OPL Simulation Tools: Anylogic 6, Vensim Database & Big Data Tools: SQL, Qubole, AWS, PySpark