FLEX Senior Manager, Data Scientist, Optimization

Marriott • Bethesda, MD

1d • $48 - $76

About The Position

The FLEX Senior Manager, Data Scientist, Optimization develops and deploys advanced mathematical optimization solutions that translate complex business and operational challenges into scalable decision applications. The role combines expertise in optimization modeling and algorithm implementation to address inventory, yielding, capacity, and resource allocation problems. It partners with business, product, engineering, and data science teams to deliver robust, production-ready solutions with measurable business impact.

The position develops and maintains optimization models and applications, supports their deployment and operation in production, and provides technical leadership on modeling practices, solution design, and algorithmic performance. This is a temporary assignment through 12/31/2027.

Requirements

• Master's degree in Operations Research, Optimization, Computational Mathematics, or a closely related quantitative discipline.
• At least 6 years of experience developing and implementing mathematical optimization models using Python and commercial optimization solvers such as Gurobi.
• Strong understanding of optimization theory, including linear programming, mixed-integer programming, network optimization, exact and heuristic algorithms, and algorithmic performance.
• Advanced proficiency in Python and SQL, with experience developing production-quality, maintainable code.
• Demonstrated experience deploying and supporting optimization solutions in production environments.
• Cross-functional collaboration skills to partner with business, product, engineering, and data science stakeholders and translate requirements into scalable solutions.

Nice To Haves

• Industry experience formulating complex business problems as mathematical optimization models and deploying solutions using commercial solvers at scale.
• Experience diagnosing model weaknesses and reformulating models through tighter bounds, stronger constraints, decomposition methods, and other modeling techniques.
• Knowledge of nonlinear programming, stochastic optimization, or robust optimization.
• Experience with Snowflake and AWS for data processing, model execution, and solution deployment.

Responsibilities

• Formulate complex business and operational problems as mathematical optimization models.
• Translate business requirements into scalable, mathematically rigorous optimization applications.
• Develop, maintain, and enhance linear programming, integer programming, and network optimization models for inventory, yielding, capacity, and resource allocation decisions.
• Build and deploy optimization applications using commercial solvers such as Gurobi and open-source solvers when appropriate.
• Apply advanced optimization techniques, including constraint reformulation and decomposition, to improve application performance.
• Analyze solver logs to diagnose and resolve model infeasibility, numerical instability, convergence issues, and runtime bottlenecks.
• Perform scenario analysis and sensitivity testing to validate model outputs, solution robustness, and business impact.
• Acquire, prepare, and validate large datasets for optimization workflows and analytical decision-making.
• Develop and maintain data pipelines and validation processes that support reliable optimization solutions.
• Use Snowflake and AWS to access, process, and manage large-scale data for model development, execution, and production workflows.
• Create visualizations and reporting to communicate model recommendations, performance, and business outcomes.
• Develop production-quality Python code and reusable optimization tools for scalable solution delivery.
• Implement testing, monitoring, and governance processes to ensure model accuracy, reliability, and maintainability.
• Collaborate with engineering, data science, product, and business teams to operationalize optimization solutions.
• Document model assumptions, methodologies, validation results, and implementation approaches.
• Provide technical leadership and guidance on optimization modeling practices, solution design, and algorithmic performance.

Benefits

• 401(k) plan
• Stock purchase plan
• Discounts at Marriott properties
• Commuter benefits
• Employee assistance plan
• Childcare discounts
• Medical coverage (full-time positions)
• Dental coverage (full-time positions)
• Vision coverage (full-time positions)
• Health care flexible spending account (full-time positions)
• Dependent care flexible spending account (full-time positions)
• Life insurance (full-time positions)
• Disability insurance (full-time positions)
• Accident insurance (full-time positions)
• Adoption expense reimbursements (full-time positions)
• Paid parental leave (full-time positions)
• Washington employees accrue paid sick leave and PTO and are eligible for a minimum of 9 holidays annually.

What This Job Offers

• Career Level: Senior