I
Insight Global
Data Scientist
Skills
Google Cloud PlatformSQL QueriesPythonAWSAzure
1 day ago
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Important information
Contract type:
Permanent
Salary:
$130,000 – $140,000 / year
Location:
Boca Raton, FL, USA
Work mode:
Onsite
Published on:
22 October 2026
What they need
Position: Data Scientist
Location: Boca Raton, FL (On-site)
MUST HAVE:
- Bachelor's Degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or related field or equivalent years of experience
- Master's Degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or related field or equivalent years of experience
- 3-6 years’ experience in Operations Research / Optimization or related fields preferred
- Hands-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 environments
- Ability to design and maintain data pipelines for large-scale modeling workflows and experience working with large, complex datasets, including feature engineering and data validation
- Proficiency in Python and SQL, with emphasis on scalable, maintainable code
- Familiarity 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 frameworks
- Design and implement large-scale optimization models, solving complex problems involving thousands to millions of variables and constraints
- Leverage solvers such as Gurobi (preferred) or equivalent tools to build high-performance solutions, including model tuning and performance optimization
- Develop end-to-end decision systems, integrating optimization outputs into production workflows and business processes
- Collaborate with business stakeholders to define objective functions, constraints, and trade-offs, ensuring solutions align with real-world decision-making
- Evaluate solution quality through scenario testing, sensitivity analysis, and stress testing of optimization results
- Scale and productionize models, including API development, automation, monitoring, and retraining workflows
- Build and maintain data pipelines to support optimization models, ensuring data quality, availability, and performance at scale
- Communicate model structure, assumptions, and results clearly to leadership, translating complex math into actionable business insights
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