Key Responsibilities:
- Develop and apply mathematical models, simulations, and optimization algorithms to improve operational processes.
- Analyze large datasets to identify trends, inefficiencies, and opportunities for improvement.
- Design and implement decision-support tools for inventory management, resource allocation, scheduling, and routing.
- Collaborate with cross-functional teams (engineering, IT, finance, logistics) to translate business problems into analytical frameworks.
- Conduct scenario analysis, risk assessment, and cost-benefit evaluations for proposed solutions.
- Present findings and recommendations to stakeholders through reports, dashboards, and presentations.
- Stay updated on emerging trends in operations research, machine learning, and AI applications in optimization.
Qualifications & Skills:
Education:
- Bachelor’s in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Computer Science, or a related quantitative field.
Experience:
- 3 years of experience in operations research, management science, or data-driven decision-making.
- Proficiency in optimization software (e.g., CPLEX, Gurobi, AMPL) and programming (Python, R, MATLAB, SQL).
- Familiarity with simulation tools (Arena, Simio, AnyLogic) and machine learning techniques is a plus.
- Experience in industries like logistics, manufacturing, healthcare, or finance is preferred.
Soft Skills:
- Strong problem-solving and critical-thinking abilities.
- Excellent communication skills to explain technical concepts to non-technical stakeholders.
- Ability to work independently and in collaborative environments.
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