FLEX Senior Manager, Data Scientist, Optimization

Additional Information
Job Number26134045
Job CategorySales & Marketing
Location7750 Wisconsin Avenue, Bethesda MD 20814, United States VIEW ON MAP
ScheduleFull Time
Located Remotely?Y
Position Type Management
Pay Range: $48.26-$75.96 per hour
Expiration Date: 11/10/2026
This is a temporary position
The assignment duration is through 12/31/2027
Job Summary
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 brings together deep expertise in optimization modeling and algorithm implementation to address inventory, yielding, capacity, and resource allocation problems. The position partners with business, product, engineering, and data science teams to deliver robust, production-ready solutions that drive measurable business impact.
CANDIDATE PROFILE Education and Experience
Required
Master's degree in Operations Research, Optimization, Computational Mathematics, or a closely related quantitative discipline.
6+ years of experience developing and implementing mathematical optimization models using Python and commercial optimization solvers such as Gurobi.
Strong understanding of optimization theory (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 to translate requirements into scalable solutions.
Preferred
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.
CORE WORK ACTIVITIES
Formulates complex business and operational problems as mathematical optimization models.
Translates business requirements into scalable, mathematically rigorous optimization applications.
Develops, maintains, and enhances linear programming, integer programming, and network optimization models supporting inventory, yielding, capacity, and resource allocation decisions.
Builds and deploys optimization applications using commercial solvers, such as Gurobi, and open-source solvers when appropriate.
Applies advanced optimization techniques such as constraint reformulation and decomposition to improve application performance.
Analyzes solver logs to diagnose and resolve model infeasibility, numerical instability, convergence issues, and runtime bottlenecks.
Performs scenario analysis and sensitivity testing to validate model outputs, solution robustness, and business impact.
Acquires, prepares, and validates large datasets required for optimization workflows and analytical decision-making.
Develops and maintains data pipelines and validation processes that support reliable optimization solutions.
Leverages Snowflake and AWS to access, process, and manage large-scale data supporting optimization model development, execution, and production workflows.
Creates visualizations and reporting that communicate model recommendations, performance, and business outcomes.
Develops production-quality Python code and reusable optimization tools that support scalable solution delivery.
Implements testing, monitoring, and governance processes to ensure model accuracy, reliability, and maintainability.
Collaborates with engineering, data science, product, and business teams to operationalize optimization solutions.
Documents model assumptions, methodologies, validation results, and implementation approaches.
Provides technical leadership and guidance on optimization modeling practices, solution design, and algorithmic performance.
At Marriott International, we are dedicated to being an equal opportunity employer, welcoming all and providing access to opportunity. We actively foster an environment where the unique backgrounds of our associates are valued and celebrated. Our greatest strength lies in the rich blend of culture, talent, and experiences of our associates. We are committed to non-discrimination on any protected basis, including disability, veteran status, or other basis protected by applicable law.
All locations offer 401(k) plan, stock purchase plan, discounts at Marriott properties, commuter benefits, employee assistance plan, and childcare discounts. Benefits are subject to terms and conditions, which may include rules regarding eligibility, enrollment, waiting period, contribution, benefit limits, election changes, benefit exclusions, and others. Click here to learn more.
Full-time positions also offer coverage for medical, dental, vision, health care flexible spending account, dependent care flexible spending account, life insurance, disability insurance, accident insurance, adoption expense reimbursements, and paid parental leave.
Washington Applicants Only: Employees will accrue paid sick leave, 0.0384 PTO balance for every hour worked and be eligible to receive minimum of 9 holidays annually.
Marriott Headquarters (HQ) supports a hybrid work environment that helps associates Be Connected. HQ based roles are generally hybrid and require regular in-office presence at the assigned location, including for candidates who live within commuting distance of HQ for a role listed as remote. Remote roles will be clearly identified in the job posting.
Marriott International is the world’s largest hotel company, with more brands, more hotels and more opportunities for associates to grow and succeed. Be where you can do your best work, begin your purpose, belong to an amazing global team, and become the best version of you.

Work arrangement
Yes