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Mathematical Optimization Remote Jobs (NOW HIRING)

Invisible Agency

$65/hr

... analysis, optimization theory, mathematical proofs, set theory, probability distributions ... Remote Seniority level: MidSenior Level

D-Wave Quantum

Senior Solution Engineer Optimization

$109K - $150K/yr

Background in a quantitative or technical field such as computer science, engineering, mathematics ... This is a remote role based in the United States but can also be a hybrid role if you are based in ...

Elder Research

Data Analyst (Remote)

Bachelor's Degree in Statistics, Applied Mathematics, Data Science, Computer Science, Operations ... Demonstrated experience with cleaning, management, optimizing performance and processing large ...

Elder Research

Data Analyst (Remote)

Bachelor's Degree in Statistics, Applied Mathematics, Data Science, Computer Science, Operations ... Demonstrated experience with cleaning, management, optimizing performance and processing large ...

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Mathematical Optimization Remote information

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$83.5K

$127K

$171K

How much do mathematical optimization remote jobs pay per year?

As of May 30, 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 are the key skills and qualifications needed to thrive as a Mathematical Optimization Specialist working remotely, and why are they important?

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 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 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.

More about Mathematical Optimization Remote jobs
What cities are hiring for Mathematical Optimization Remote jobs? Cities with the most Mathematical Optimization Remote job openings:
What are the most commonly searched types of Mathematical Optimization jobs? The most popular types of Mathematical Optimization jobs are:
What states have the most Mathematical Optimization Remote jobs? States with the most job openings for Mathematical Optimization Remote jobs include:
What job categories do people searching Mathematical Optimization Remote jobs look for? The top searched job categories for Mathematical Optimization Remote jobs are:
Mathematical Optimization Remote jobs near you
Infographic showing various Mathematical Optimization Remote job openings in the United States as of May 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $127,031 per year, or $61.1 per hour.
Staff Software Engineer, Capacity Optimization

Staff Software Engineer, Capacity Optimization

Waymo

Manhattan, NY • On-site, Remote

$251K - $310K/yr

Other

Posted 22 days ago

Job description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

Our Simulation team is at the heart of this mission, enabling us to safely and rapidly iterate on the Waymo Driver. We run billions of miles of simulations, creating a massive and complex demand for technical infrastructure resources (CPU, GPU, TPU, Storage).

We are establishing a new team called SCORPIO (SimEval Capacity Operations, Resource Planning, Infrastructure Optimization). This team is tasked with building a critical capability for Waymo: data-driven, strategic capacity planning and resource optimization. We are looking for a Quant Software Engineer at the L6 level to bridge the gap between sophisticated mathematical modeling and production-scale infrastructure automation. You will be responsible for building the technical systems that forecast demand, optimize resource allocation, and automate infrastructure management, ensuring our simulation environment is both high-performance and cost-effective.

You will:

As the founding Lead of the SCORPIO team, you will:

  • Infrastructure Modeling & Automation: Design and build production-grade systems and pipelines to automate capacity planning, demand management, and quota allocation.
  • Quantitative Forecasting: Implement and maintain sophisticated models for infrastructure demand forecasting, incorporating architectural shifts, peak loads, and time-shifting opportunities.
  • Resource Optimization Algorithms: Develop and deploy algorithms to optimize resource utilization across a heterogeneous fleet (CPU, GPU, TPU) and diverse supply models (on-demand vs. reserved).
  • Data Pipeline Engineering: Architect and maintain robust data pipelines that ingest infrastructure telemetry and demand driver signals to feed forecasting and optimization engines.
  • Outcome Analysis: Build systems to translate resource plans into tangible outcomes (e.g., queue lengths, user demand fulfillment) and develop attribution models for capacity imbalances.
  • Cross-Functional Collaboration: Partner with Simulation, Infrastructure, and Finance teams to translate business requirements into technical specifications and automated solutions.
  • Technical Leadership: Provide technical guidance on the intersection of quantitative modeling and systems engineering, mentoring junior members and influencing the technical roadmap for SCORPIO.

You have:

  • Bachelor's degree in Computer Science, Mathematics, Statistics, Operations Research, or a related quantitative field, or equivalent practical experience.
  • 8+ years of experience in software engineering, with a strong focus on distributed systems, large-scale data processing, or quantitative engineering.
  • Proficiency in C++ or Python, with experience building and deploying production-level software.
  • Experience with large-scale distributed systems and cloud infrastructure (e.g., GCP, AWS, Azure).
  • Strong background in quantitative methods, such as optimization, statistical modeling, or time-series analysis.
  • Expertise in SQL and working with large-scale data warehouses (e.g., BigQuery).

We prefer:

  • PhD or Master's degree in a quantitative field or Computer Science.
  • Experience in Capacity Engineering, Infrastructure Optimization, or Site Reliability Engineering at scale.
  • Familiarity with ML-driven forecasting and optimization techniques.
  • Experience with financial modeling or cost-benefit analysis of technical infrastructure.
  • Experience building automation tools for resource management and quota allocation.
  • Knowledge of simulation workloads or high-performance computing (HPC) environments.

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range
$251,000—$310,000 USD

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