Operation Research

Job Description

Job Title: Operations Research Scientist Key Responsibilities 1. Model Development Translate business requirements in to solid and detailed mathematical problems Design and build mathematical optimization models (like linear, integer, nonlinear programming, mixed integer linear, stochastic optimization, heuristics, dynamic programming or RL-based optimization) Develop stochastic models \ simulation models to analyse system performance and its evolution; play-out scenarios and predict behaviour under varying conditions Verify models with actual data, identify gaps, modify model parameters, fine-tune and check sensitivity for more aligned performance. 2. Implementation & Deployment Collaborate with engineering teams to integrate models into production environments, ensuring scalability and reliability Test and validate models for accuracy, usability, and alignment with business objectives Design monitoring systems to track model performance over time Iteratively improve models based on real-world feedback and changing conditions 3. Communication & Collaboration Translate complex technical concepts into clear, actionable insights for non-technical stakeholders Create compelling stories, analysis, documents and dashboards to illustrate model outputs and recommendations Present findings to executive leadership, highlighting business impact and ROI Work cross-functionally with business units to understand core operational challenges and requirements Train and support end users in interpreting and applying model outputs Required Qualifications 1. Education Master's Operations Research, Industrial Engineering, Applied Mathematics, or related field 2. Technical Skills Strong programming skills in at least one language commonly used for optimization (Python, C++, C, Java) Proficiency with optimization solvers (e.g., Gurobi, CPLEX etc) Competent in developing mathematical optimization models using mathematical modeling languages such as OPL, GAMS, AMPL or develop with Pyomo, Gurobipy, etc. Proficient in code driven simulation models and software driven (AnyLogic, Arena etc) Experience with statistics, data analytics and visualization 3. Experience 3+ years experience applying OR techniques to solve business problems 4. Soft Skills Ability to translate high-level requirements and deadlines into shorter-term work tasks, self-direct work and collaborate Excellent communication skills with demonstrated ability to explain complex concepts to non-technical audiences Experience deploying models in production and real-world environments Preferred Qualifications PhD in Operations Research, Applied Mathematics, or related field Experience with cloud computing platforms (AWS, Azure, GCP) Ability to analyse system design and process design, and build wholistic solutions Knowledge of machine learning techniques and their integration with OR approaches Familiarity with visualization tools (Tableau, Power BI) and dashboard creation Industry experience in logistics, airlines, supply chain, manufacturing, or healthcare Publications in relevant conferences or journals Success in this Role The ideal candidate doesn't just build elegant models that work in theory but creates practical solutions that deliver real business value in complex, dynamic environments. They posses strong analytical skills and Role & responsibilities Preferred candidate profile