Data Scientist

Position: Data ScientistLocation: Boca Raton, FL (On-site)

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MUST HAVE:Bachelor's Degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or related field or equivalent years of experienceMaster's Degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or related field or equivalent years of experience3-6 years’ experience in Operations Research / Optimization or related fields preferredHands-on experience with Gurobi (strongly preferred) or similar solvers (CPLEX, OR-Tools, etc.)Proven experience building and deploying large-scale mathematical models (LP, MILP, etc.) in production environmentsAbility to design and maintain data pipelines for large-scale modeling workflows and experience working with large, complex datasets, including feature engineering and data validationProficiency in Python and SQL, with emphasis on scalable, maintainable codeFamiliarity with cloud environments (AWS, Azure, GCP) for scalable execution
D2D:Formulate decision problems as mathematical optimization models (LP, MILP, MINLP), translating business constraints and objectives into structured frameworksDesign and implement large-scale optimization models, solving complex problems involving thousands to millions of variables and constraintsLeverage solvers such as Gurobi (preferred) or equivalent tools to build high-performance solutions, including model tuning and performance optimizationDevelop end-to-end decision systems, integrating optimization outputs into production workflows and business processesCollaborate with business stakeholders to define objective functions, xzbcwsv constraints, and trade-offs, ensuring solutions align with real-world decision-makingEvaluate solution quality through scenario testing, sensitivity analysis, and stress testing of optimization resultsScale and productionize models, including API development, automation, monitoring, and retraining workflowsBuild and maintain data pipelines to support optimization models, ensuring data quality, availability, and performance at scaleCommunicate model structure, assumptions, and results clearly to leadership, translating complex math into actionable business insights