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Full Time
1. Develop mathematical models and algorithms for optimization problems (LP, IP, MIP, NLP, QP)across various domains, such as supply chain management, resource allocation, scheduling, and routing.
2. Implement optimization solutions using Python and optimize code for performance and scalability.
3. Collaborate with data scientists, engineers, and business stakeholders to understand requirements, gather data, and define optimization objectives and constraints.
4. Conduct thorough analyses of data sets, system performance metrics, and operational processes to identify optimization opportunities and areas for improvement.
5. Design experiments and simulations to evaluate the effectiveness and robustness of optimization algorithms and validate proposed solutions.
6. Work closely with software development teams to integrate optimization models and algorithms into production systems and applications.
7. Monitor the performance of deployed optimization solutions, analyse results, and iterate on algorithms to achieve desired outcomes.
8. Communicate findings, insights, and recommendations to stakeholders through presentations, reports, and documentation.
1. Bachelor s or master s degree in computer science, operations research, engineering, mathematics, or a related field.
2. Solid understanding of optimization theory, mathematical modelling, and algorithm development.
3. Proficiency in Python programming.
4. Experience with optimization libraries and frameworks, such as SciPy, NumPy, Gurobi, or CPLEX.
5. Strong analytical and problem-solving skills, with the ability to translate complex problems into actionable insights and solutions.
6. Experience working with large-scale data sets, databases, and distributed computing environments.
7. Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
EY
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