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Company Overview
A leading global technology and operations organization is seeking a Senior Data Scientist to support its mathematical optimization and operations research initiatives. The organization focuses on delivering advanced analytical solutions that improve operational efficiency, predictive decision-making, and business outcomes across complex, data-driven environments.
Summary
This Senior Data Scientist position specializes in mathematical optimization and operations research, expanding on prior data science and machine learning expertise to include exact and approximate methods for linear and nonlinear optimization problems. The role combines technical modeling, solution deployment, and cross-functional collaboration to drive measurable operational impact.
Key Responsibilities
Collaborate with cross-functional teams, including business stakeholders, domain experts, and engineers, to identify and frame complex optimization and operations research problems
Design, develop, and deploy optimization solutions impacting aircraft assignment, crew scheduling, and related operational areas, including predictive models for demand forecasting, disruptions, or operational KPIs
Validate models and solutions through rigorous testing, scenario analysis, and sensitivity studies; clearly communicate results and trade-offs to technical and non-technical audiences
Work closely with application development teams to operationalize optimization capabilities, advising on data requirements, API design, performance, and monitoring
Monitor and maintain production optimization services, troubleshoot issues, and iterate models and algorithms as business needs evolve
Stay current on advances in operations research, optimization solvers (e.g., Gurobi), algorithmic improvements, and data science techniques; evaluate and recommend new tools or libraries where beneficial
Requirements
BS in Computer Science, Mathematics, Physics, or a related discipline required; MS or PhD in mathematical optimization highly desired
Advanced programming skills in Python and familiarity with data structures, algorithm design/analysis, and object-oriented programming
At least 2 years of technical experience in two or more of the following areas: operations research (linear/integer/mixed-integer programming), predictive modeling, shallow machine learning, and information retrieval
Familiarity with simulation, queuing theory, network, and decision analyses is a plus
Knowledge of optimization algorithms, including gradient-based and metaheuristic methods
Experience with Python optimization libraries such as NumPy, SciPy, CVXPY, PuLP, Pyomo, and platforms such as Gurobi, CPLEX, or Google OR-Tools
Hands-on experience with AWS, GCP, or similar public cloud environments is advantageous
Prior experience or knowledge in aviation or airline operations is a plus
Excellent interpersonal and communication skills for collaboration with technical and non-technical stakeholders
Experience with Agile, Scrum, or Kanban methodologies is desirable
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