We are looking for an experienced Data Scientist with strong expertise in mathematical optimization and Operations Research, with hands-on experience using Gurobi.

The ideal candidate should have strong programming skills in Python and SQL, along with experience in developing and implementing optimization models to solve complex business problems.

Key Responsibilities
• Design, develop, and implement optimization models using Gurobi.
• Translate complex business problems into mathematical and optimization models.
• Work on optimization techniques such as:
• Linear Programming
• Integer / Mixed Integer Programming
• Nonlinear Optimization
• Large-Scale Optimization
• Develop scalable solutions using Python.
• Perform data extraction, analysis, and manipulation using SQL.
• Evaluate optimization model performance and improve solution efficiency.
• Collaborate with business, data science, and engineering teams to understand requirements and deliver optimization-driven solutions.
• Perform model validation, testing, and performance tuning.
• Document optimization logic, assumptions, solution approaches, and results.
• Support deployment and integration of optimization models into production environments.

Mandatory Skills
• 6+ years of overall experience in Data Science, Optimization, Operations Research, or a related area.
• Strong hands-on experience with Python.
• Strong proficiency in SQL.
• Hands-on experience in Gurobi Optimization.
• Good understanding of mathematical optimization concepts.
• Experience working with optimization models in real-world business scenarios.
• Strong analytical and problem-solving skills.

Good to Have
• Experience with AWS.
• Experience using Git for version control.
• Exposure to Harness or similar CI/CD tools.
• Strong background in Operations Research.
• Experience deploying optimization models in production environments.

Preferred Academic Background

Bachelor’s or Master’s degree in:
• Operations Research
• Industrial Engineering
• Computer Science
• Data Science
• Mathematics / Applied Mathematics
• Related quantitative discipline

Candidates should preferably have academic or practical exposure to:
• Linear Programming
• Integer Programming
• Mixed Integer Programming
• Large-Scale Optimization
• Nonlinear Optimization

Preferred Candidate Profile

The candidate should be comfortable working on complex optimization problems and should be able to independently understand business constraints, formulate mathematical models, implement them in Gurobi, and interpret the results for business stakeholders.