Mathematical Optimisation Engineer

At NEORIS, now part of EPAM Systems, we are a Digital Accelerator that helps companies step into the future. With more than 20 years of experience as Digital Partners to some of the world’s leading organizations, we operate with a multicultural, startup-driven culture that fosters innovation, continuous learning, and the delivery of high-impact solutions. We are more than 4,000 professionals across 11 countries, committed to transforming business through technology and advanced engineering.

• →Design, develop, and implement mathematical optimization models for scheduling and planning solutions in Operations and Manufacturing environments.
• →Translate complex business challenges into structured mathematical modelling and constrained optimization problems.
• →Build, test, and deploy scalable optimization engines into production environments.
• →Collaborate with engineering and product teams to deliver robust, high-performance OR-based systems at scale.
• →Promote best practices in operations research, software engineering, and model validation across technical teams.
• →Communicate analytical findings and optimization strategies to both technical and non-technical stakeholders.

• Bachelor’s or Master’s degree in Operations Research, Computer Science, Mathematics, Engineering, or related field.
• Minimum 3 years of hands-on experience in constrained optimization and mathematical modelling in industry.
• Proven experience with optimization solvers such as Gurobi, CPLEX, LocalSolver, or Google OR-Tools.
• Strong programming skills in Python.
• Experience deploying optimization applications to production environments with real-world users.
• Solid understanding of software development practices (CI/CD, automated testing, version control, branching strategies).
• Ability to work with loosely defined requirements and transform them into well-structured optimization models.
• Advanced English proficiency (spoken and written).

• Experience in Healthcare or Financial services domains.
• Knowledge of large-scale distributed systems or cloud-based architectures.
• Experience designing analytical engines for enterprise-scale environments.
• Postgraduate studies or certifications related to Operations Research, Optimization, or Advanced Analytics.