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Dynamic Stochastic Optimization Jobs (NOW HIRING)

Neura Market

$251K - $310K/yr

... of dynamics (system response, mechanics, system modelling) , optimization (gradient descent, linear algebra, filtering), control (linear, state space, stochastic, feedback control), operations ...

New

Talanto

$251K - $310K/yr

... of dynamics (system response, mechanics, system modelling) , optimization (gradient descent, linear algebra, filtering), control (linear, state space, stochastic, feedback control), operations ...

MCKESSON

Sr. Data Scientist, Ops Research

Irving, TX · On-site

$136K - $227K/yr

... stochastic process simulation and optimization solutions at McKesson, as well as make significant ... Familiarity with reinforcement learning or approximate dynamic programming techniques. * Experience ...

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Dynamic Stochastic Optimization information

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$16K

$55.8K

$102K

How much do dynamic stochastic optimization jobs pay per year?

As of Sep 10, 2026, the average yearly pay for dynamic stochastic optimization in the United States is $55,794.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,000.00 and $72,500.00 per year, depending on experience, location, and employer.

What is dynamic stochastic optimization?

Dynamic stochastic optimization is a mathematical approach used to make optimal decisions over time in situations where outcomes are uncertain and may change. It combines dynamic programming (making a sequence of decisions) with stochastic modeling (accounting for randomness). This method is widely used in fields like finance, engineering, and operations research to solve problems such as investment planning, resource allocation, and supply chain management. By modeling uncertainties and the evolution of systems over time, it helps decision-makers find strategies that maximize expected performance or minimize risk.

What are the key skills and qualifications needed to thrive as a dynamic stochastic optimization specialist?

To thrive as a Dynamic Stochastic Optimization Specialist, you need a solid background in mathematics, statistics, operations research, and computer science, typically supported by an advanced degree in a quantitative field. Proficiency with programming languages (such as Python, MATLAB, or R), optimization software (like Gurobi or CPLEX), and familiarity with simulation tools are essential. Strong analytical thinking, creative problem-solving, and effective communication skills help you translate complex models into actionable insights. These competencies are crucial for designing, implementing, and communicating robust optimization models that drive decision-making in uncertain and dynamic environments.

What are the typical collaboration opportunities for professionals working in dynamic stochastic optimization roles?

Professionals in Dynamic Stochastic Optimization often collaborate closely with data scientists, software engineers, and domain experts to develop and implement optimization models that adapt to uncertainty over time. They may also work with decision-makers or operational teams to translate complex mathematical solutions into actionable strategies. This interdisciplinary collaboration helps ensure that the models are both mathematically sound and practical for real-world applications, such as supply chain management, finance, or energy systems.

What is the difference between Dynamic Stochastic Optimization vs Data Analyst?

AspectDynamic Stochastic OptimizationData Analyst
Required CredentialsAdvanced degrees in Operations Research, Mathematics, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentQuantitative teams, research labs, or analytics departmentsBusiness units, marketing, finance, or operations teams
Industry UsageSupply chain, finance, energy, and logisticsMarketing, finance, healthcare, and retail sectors
Search & Comparison IntentUnderstanding optimization techniques for decision-making under uncertaintyAnalyzing data to inform business decisions

Dynamic Stochastic Optimization focuses on developing models to make optimal decisions in uncertain environments, often requiring advanced mathematical skills. Data Analysts interpret and analyze data to support business strategies. While both roles involve data, their applications, skills, and industries differ significantly.

What other helpful pages are available for Dynamic Stochastic Optimization?

Other pages related to Dynamic Stochastic Optimization:

Infographic showing various Dynamic Stochastic Optimization job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.

Staff Software Engineer, Fleet Optimization

San Francisco, CA • On-site

Waymo
Internet and IT • 1 - 5K employees
Learn more about Waymoexternal

$251K - $310K/yr

Full-time

Posted 9 days ago

Key responsibilities

  • Develop algorithms, design systems, and implement software to solve problems related to fleet management and optimization.

  • Instrument systems and analyze complex datasets to understand behaviors, troubleshoot issues, and evaluate hypotheses.

  • Build, operate, and improve mission-critical tools and systems responsible for the continuous optimization of fleet operations.

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 Driverâ„¢-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.
You will:
  • Algorithm development, system design, and software implementation to solve multi-disciplinary problems at the intersection of computer science, optimization, and fleet management.
  • Instrument systems and analyze complex datasets in order to understand behaviors, troubleshoot problems, identify opportunities, and evaluate hypotheses and counterfactual scenarios.
  • Evaluate and reason about optimization and forecasting system performance, including sensitivity to inputs, fidelity of output actuations, and interactions with other automated and human systems.
  • Build, evolve, own, and operate mission-critical tools and systems responsible for the continuous optimization of fleet operations.
  • Collaborate with Depot Operations, Product, UX, Data Science, and other Engineering teams to develop and improve automated systems, operational processes, and documentation as business needs grow and evolve.

You have:
  • BS degree in Computer Science or related field.
  • 5+ years of direct coding experience. Backend or infrastructure preferred.
  • Experience with backend coding languages: C++, (secondary Python).
  • Professional experience building and analyzing quantitative software systems such as those involving algorithmic optimization, machine learning, or large-scale data analytics.

We prefer:
  • Experience implementing algorithms for multidimensional systems informed by practical knowledge in any of the fields of dynamics (system response, mechanics, system modelling) , optimization (gradient descent, linear algebra, filtering), control (linear, state space, stochastic, feedback control), operations research (constraint optimization, Linear programming) and/or implementing design patterns.
  • Passion for working in cross functional environments that include nontechnical stakeholders
  • Familiarity with Google infrastructure (e.g. Flume, Borg, Protocol Buffers, OnePlatform) or the equivalent non-Google technologies
  • Experience with operations tooling, developer productivity, or developer tools
  • Strong bias for action.

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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