54 Mathematical Modeling Jobs - Page 3

Overseeing the manufacturing process, ensuring quality, and installing mechanical components and systems Analyzing data, and evaluating the performance of mechanical designs and systems. Troubleshooting malfunctions, conducting root cause analysis,

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

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SENIOR OPTIMIZATION ENGINEER Hyderabad Role Senior Optimization Engineer Contract type Permanent About the role As a Senior Optimization Engineer you provide technical expertise in the area of numerical optimization of thermo-fluid systems which are core to the Company's business this includes trade-off and optimize energy efficiency, production cost and operating economy. You engage with global product teams to solicit business needs and convert those into computational decision-making workflows, methods and tools to radically impact how company's products are designed, deployed and operated. Key targets include improving engineering effectiveness as well as developing disruptive, innovative methods for model-based design and operation of company's systems. You also take active part in product development to support design engineers in adopting and using new methods and tools. You also work closely with other teams in Systems, Controls, ML/AI COE, including teams responsible for model development (to drive the development of optimization-friendly thermo-fluid models) and controls engineering (to promote the use of computational optimization strategies (MPC, RTO) as needed). We are offering you We are committed to offering competitive benefits programs for all of our employees and enhancing our programs when necessary. A dynamic and international work environment in a company with high technology products. A strong growth strategy and people who are passionate about what they do. Requirements Education MEng or PhD in a relevant Engineering discipline (e.g., applied mathematics, mechanical or chemical engineering) with 5+ years of experience. Skills and qualifications Proven ability to capture engineering design and operation problems as mathematical programming problems (NLPs), including attention to reliable convergence of such problems. Proficient with the mathematical theory (applied mathematics, numerical analysis and functional analysis), algorithmic foundations (notably existence and convergence proofs), and methods/tools for numerical optimization (SQP, interior point method, etc.) of large-scale systems. Experience from using common algorithms/solvers for large-scale gradient-based non-linear programs, e.g., IPOPT, CONOPT, KNITRO, and WORHP, including their respective applicability to different types of problems. Experience from formulating and solving discrete optimization problems and using common algorithms, including CPLEX and Gurobi. Familiarity with physics-based modeling principles and best practices of thermo-fluid systems, such as vapor compression cycles or power plants. Familiarity and experience with development of computational platforms and tools in Python or equivalent. Familiarity with using HPC and cloud-based platforms for computation at scale. Demonstrated ability to work as part of a multidisciplinary team and an entrepreneurial attitude towards technological innovation in a global environment. Self-starter who is well-organized in an international team environment, with proven communication skills. Responsibilities Deployment. Support that methods and tools developed in the group impact the company's business through engagement in global product projects, including capture and formulation of computational problems arising in such projects. Methods, tools and algorithms. Ensure that appropriate computational methods, tools and algorithms for large-scale numerical optimization are based on sound mathematical foundations and are deployed to match the needs of the company's business, including contributing to the architecture, development, testing and documentation of the methods and tools developed in the group. Modeling for optimization. Support development of mathematical models for thermo-fluid systems are built based on principles and best practices that secure reliable application of numerical optimization algorithms. Talent. Support development and training of staff within company's product teams and within the Computational Engineering group; contribute to talent pipeline by supervising student internships and theses.