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Optimization Scientist Jobs (NOW HIRING)

DEFCON AI

Software Project Lead

You will not be alone: a program manager owns customer cadence, a subject-matter expert owns the mission content, and an optimization scientist owns the analytic core. Your job is to coordinate their ...

RPS Softwares AB

NY · On-site

$100 - $125/hr

We are hiring Senior Optimization Data Scientist for Sweden. Job Summary: We are seeking an experienced Optimization Data Scientist with strong expertise in Linear & Mixed Integer Programming ...

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How much do optimization scientist jobs pay per year?

As of Sep 9, 2026, the average yearly pay for optimization scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is an optimization scientist?

An Optimization Scientist is a professional who uses mathematical models, algorithms, and data analysis techniques to improve processes, systems, or products. They work in various industries to identify inefficiencies and develop solutions that maximize performance, minimize costs, or achieve specific objectives. Their work often involves operations research, machine learning, and computer programming to solve complex problems and support decision-making. Optimization Scientists collaborate with engineers, analysts, and business leaders to implement and monitor solutions. Their goal is to help organizations operate more efficiently and effectively.

What are the key skills and qualifications needed to thrive as an optimization scientist, and why are they important?

To thrive as an Optimization Scientist, you need a solid background in mathematics, operations research, and data analysis, typically supported by an advanced degree in a quantitative field. Familiarity with optimization software (like Gurobi or CPLEX), programming languages such as Python or R, and experience with modeling tools are crucial. Strong problem-solving, communication, and collaboration skills help translate complex data into actionable business solutions. These competencies are vital for designing efficient systems and providing measurable improvements in operational performance.

How does an optimization scientist typically collaborate with cross-functional teams to implement solutions?

Optimization Scientists often work closely with data engineers, software developers, and business stakeholders to design and implement effective optimization models. They translate complex analytical findings into actionable solutions, ensuring that technical recommendations align with business goals. Regular communication and collaboration are essential, as Optimization Scientists may need to explain model assumptions, gather domain knowledge, and adjust their approaches based on feedback from other teams. This interdisciplinary teamwork not only enhances solution quality but also helps in the smooth adoption of optimization strategies across the organization.

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Cities with the most Optimization Scientist job openings:

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Infographic showing various Optimization Scientist job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 9% Part Time, and 3% Contract. Highlights an 78% Physical, 5% Hybrid, and 17% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Optimization Scientist

Boston, MA • On-site

Recentive Analytics Inc.
See more jobs at Recentive Analytics Inc.external

$100 - $125/hr

Other

Posted 21 days ago

Job description

Optimization Scientist

Department: Engineering

Employment Type: Full Time

Location: SF / Boston / Remote (USA)

Description

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.

What You’ll Be Doing
  • Advanced Optimization Model Development: Designing and building advanced optimization models, leveraging techniques like integer programming, network flow, and metaheuristics.
  • 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.
What We’re Looking For
  • 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.
Why Work at Recentive

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.

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