Senior Optimization Scientist / Operations Research Scientist
Why This Role Stands Out
This hybrid role at InnoCore Solutions offers a fantastic opportunity to drive impactful improvements in workforce planning and task assignment by developing cutting-edge optimization models, with a competitive salary and excellent growth potential. You'll thrive here if you have a strong background in mathematical optimization and are eager to leverage advanced tools and collaborate with dynamic teams to solve complex operational challenges. Apply today to contribute to innovative solutions and advance your career in a supportive environment.
Quick Overview
Job Description
Responsibilities:
- Work with business, Operations Research, and IT teams to understand requirements and translate business rules into mathematical optimization models.
- Develop, maintain, and improve Mixed Integer Programming (MIP) models for task assignment and workforce planning.
- Build and integrate optimization models using FICO Xpress, Gurobi, or CPLEX.
- Tune solver performance and improve model runtime, solution quality, and scalability.
- Analyze solver logs, model inputs/outputs, and data to identify performance, data-quality, and feasibility issues.
- Troubleshoot modeling issues such as conflicting constraints, incorrect defaults, and infeasible solutions.
- Validate and benchmark optimization results against business requirements and manual processes.
- Develop and maintain Python/Streamlit dashboards to visualize optimization results.
- Write clean, tested, and maintainable production-quality code.
- Work closely with Java engineers to integrate and productionize optimization models.
- Use AI coding tools such as GitHub Copilot or Claude to improve development speed while maintaining code quality.
- Communicate model results and trade-offs effectively with both technical and business teams.
Requirements:
- 5+ years of experience in Operations Research, Mathematical Optimization, Data Science, or a related quantitative field.
- Strong hands-on experience with MIP / mathematical optimization.
- Experience developing and deploying optimization models into production.
- Strong knowledge of linear programming, integer programming, constraints, and objective functions.
- Experience with FICO Xpress, Gurobi, or CPLEX. FICO Xpress is highly preferred.
- Experience with Java and/or Python for optimization model development.
- Experience with solver tuning, model performance optimization, and troubleshooting infeasible models.
- Strong data analysis and problem-solving skills.
- Experience working with large datasets; Azure ADLS experience is preferred.
- Experience with Python/Streamlit or similar data visualization tools.
- Strong communication and teamwork skills.
Education:
- Bachelor's degree or PhD in Operations Research, IndustrialEngineering, Applied Mathematics, Optimization, Computer Science, Engineering, Statistics, Data Science, or a related field.
Skills
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