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Mathematical Optimization Remote Jobs (NOW HIRING)

Gurobi Optimization

Senior MIP Developer (Global Remote)

$55.75 - $73.75/hr

A mission that focuses on mathematical optimization. We empower our customers to expand their use ... Content with operating from a home office in a remote work environment. * Flexible and willing to ...

Intersect

Optimization Engineer

$217K - $237K/yr

... our flexible remote culture. About This Role Intersect is building the integrated energy ... mathematical foundation. * Strong knowledge of energy systems, wholesale power markets, or power ...

Brain Gain Recruiting

Explainable AI Engineer

Palo Alto, CA · Remote

$122K - $165K/yr

Mathematical optimization * Decision and Control * Experience with MATLAB * Model-based development ... This is a remote position. USA, Nationwide. * You will have an opportunity to start as a contractor ...

Fix-It Group

SEO Specialist

Golden, CO · On-site +1

$90K/yr

SEO Specialist Compensation: $90,000 per year Status: Full-Time, Exempt, Remote Must be US based ... Math and Yoast SEO and partnering with development resources when needed. Local SEO & Google ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site +1

You'll also harness mathematical optimization to identify the most profitable business strategies ... Team members who choose virtual / remote work should have an adequate space to serve as their home ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site +1

You'll also harness mathematical optimization to identify the most profitable business strategies ... Team members who choose virtual / remote work should have an adequate space to serve as their home ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · Remote

You'll also harness mathematical optimization to identify the most profitable business strategies ... Team members who choose virtual / remote work should have an adequate space to serve as their home ...

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Mathematical Optimization Remote information

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How much do mathematical optimization remote jobs pay per year?

As of Sep 11, 2026, the average yearly pay for mathematical optimization remote in the United States is $127,031.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,000.00 and $143,500.00 per year, depending on experience, location, and employer.

What is a mathematical optimization remote job?

A Mathematical Optimization Remote job involves using mathematical techniques and algorithms to solve optimization problems, such as maximizing efficiency or minimizing costs, while working from a remote location. Professionals in this field apply optimization theory, modeling, and computational methods to real-world problems in industries like logistics, finance, engineering, and data science. Remote roles allow for flexibility, enabling collaboration with teams and clients online while leveraging specialized software and programming languages such as Python, MATLAB, or R.

What are the key skills and qualifications needed to thrive as a mathematical optimization specialist working remotely?

To thrive as a Mathematical Optimization Specialist in a remote setting, you need a strong background in mathematics, operations research, or computer science, often supported by an advanced degree. Proficiency with optimization software (such as Gurobi, CPLEX, or MATLAB), programming languages like Python or R, and familiarity with cloud-based collaboration tools is typically required. Excellent problem-solving abilities, self-motivation, and clear communication skills help you stand out when collaborating with distributed teams and stakeholders. These skills and qualities are crucial for efficiently developing, implementing, and explaining optimization solutions in a remote work environment.

What are some common challenges faced by professionals in remote mathematical optimization roles, and how can they be addressed?

Remote mathematical optimization professionals often encounter challenges such as limited real-time collaboration with team members, managing complex problem-solving tasks independently, and ensuring effective communication of technical findings to non-technical stakeholders. To address these challenges, it's helpful to establish regular virtual meetings, use collaborative tools for sharing code and results, and develop clear documentation. Additionally, proactively seeking feedback and staying engaged with the broader team can help maintain alignment and foster innovation.

What is the difference between Mathematical Optimization Remote vs Data Analyst Remote?

AspectMathematical Optimization RemoteData Analyst Remote
Required CredentialsDegree in Mathematics, Operations Research, or related field; proficiency in optimization softwareDegree in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentRemote, often collaborative with teams on complex modeling projectsRemote, focused on data collection, visualization, and reporting
Industry UsageFinance, logistics, supply chain, tech companiesMarketing, finance, healthcare, tech companies
Common Search/ComparisonYesNo

Mathematical Optimization Remote specialists focus on developing algorithms to optimize processes and decision-making, often requiring advanced mathematical skills. Data Analysts Remote interpret data to provide insights, using statistical tools. While both roles are remote and involve data, they differ in technical focus and industry applications.

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Mathematical Optimization Remote jobs near you
Infographic showing various Mathematical Optimization Remote job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 89% Full Time, 8% Part Time, and 2% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution, with an average salary of $127,031 per year, or $61.1 per hour.

R&D Data Scientist: Mathematical Modeling and Optimization

Austin, TX • Remote

Liftlab Analytics, Inc.
See more jobs at Liftlab Analytics, Inc.external

Full-time

Re-posted 27 days ago

Job description

(Fully-remote US position)
About LiftLab

Liftlab is the leading provider of science-driven software to optimize marketing spend and predict revenue for optimal spend levels. We call this the Science of Marketing Effectiveness. Our platform combines economic modeling with specialized media experimentation so brands and agencies can clearly see the tradeoffs of growth and profitability. With decades of experience in marketing analytics and data science, our team of industry experts and thought leaders is proud to enable leading and emerging brands such as Cinemark, Express, Hanna Anderson, Lulu & Georgia, Pandora, Sephora, Skims, Tory Burch, Thrive, and Vionic, with our cutting-edge solutions and strategic guidance.

Job responsibilities

  • Develop new algorithm-based features of LiftLab's marketing measurement and optimization platform

  • Performs diagnostics and root-cause analysis and provide fixes

  • Works with Data Science and Engineering to implement these features into LiftLabs product and workflow

Course work/experience:

  • Data manipulation

    • SQL

    • Operating on big datasets in Python

    • Data visualization

  • Mathematical optimization

    • Linear optimization concepts

    • Nonlinear continuous optimization

    • Linear algebra

  • Mathematical modeling

    • Using parametrized systems of equations to represent real-world systems

  • Statistics

    • Multivariate regression

    • Clear understanding of Maximum Likelihood estimation and computational methods to find MLE parameters

    • Bayesian concepts

    • Hypotheses testing

Education requirements

Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field. We will consider holders of Bachelor degrees with relevant experience

Skills/Aptitude

  • Engineering and detective mindset

    • Both to diagnose data and existing algorithms and to develop new analytics functionality

  • Pragmatic approach to real-world problems

  • Focus on problem solving over applying specific models

  • Willingness to make approximations and assumptions rather than find "the" optimal solution

  • Ability to combine multiple techniques and models to solve end-to end-problems

  • Communication and collaboration skill

  • Ability to convert non-technical requests into project specifications

Apply