Optimization Scientist

Optimization Scientist

Department: Engineering

Employment Type: Full Time

Location: SF / Boston / Remote (USA)

We’re looking for a Optimization Scientist to join Recentive’s core Operations Research team. In this role, you’ll develop and deploy optimization models that solve complex scheduling, resource allocation, and decision‑making problems for some of the biggest names in sports and entertainment. You’ll work closely with engineering and data teams to design analytical solutions that drive measurable impact across industries.

• Advanced Optimization Model Development: Designing and building advanced optimization models, leveraging techniques like integer programming, network flow, and meta heuristics.
• Cross‑Functional
  
  Collaboration:
  
  Collaborating with cross‑functional teams to define problems, develop solutions, and integrate optimization models into production systems.
• Real‑World Application & Deployment: Prototyping and deploying models to solve real‑world problems in areas like scheduling, resource optimization, and forecasting.

• Operations Research & Optimization Expertise: 5+ years of experience in operations research and optimization model development in a production environment.
• Mathematical Programming
  
  Experience:
  
  Strong expertise in mathematical programming, including integer programming, decomposition methods, and cutting‑plane methods.
• Combinatorial Optimization
  
  Experience:
  
  Experience tackling large‑scale combinatorial optimization problems with creative modeling techniques.
• Production‑Ready Development: Proficiency in Python for developing scalable, production‑ready optimization solutions.
• Solver & Framework Familiarity: Hands‑on experience with commercial optimization solvers (e.g., Gurobi, CPLEX) and open‑source frameworks.
• Iterative Problem‑Solving Approach: A results‑driven mindset with the ability to prototype quickly and iteratively refine solutions.

Impactful Work: Our technology and products directly shape operational strategies at leading sports teams and leagues, broadcasters, and other key players in the live events ecosystem.

Forward Thinking: Design and build forward‑thinking analytical solutions that blend creativity and engineering—leveraging advanced algorithms, optimization, and machine learning to solve complex, real‑world challenges.

Collaborative Culture: We’re a growing, tight‑knit data‑centered team that values knowledge‑sharing, learning, and innovation.

Growth & Ownership: Shape your career as a technical leader while helping build next‑generation analytical tools from the ground up.