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Dynamic Stochastic Optimization Jobs (NOW HIRING)

Altera

Senior FPGA Compiler Software Engineer

San Jose, CA · On-site

$178K - $259K/yr

Experience with combinatorial/continuous optimization, including but not limited to Boolean SAT, stochastic search-based methods, numerical methods for continuous optimization, dynamic programming ...

Cellanome

Machine Learning Engineer

Foster, OR · On-site +1

$160K - $215K/yr

Experience applying algorithmic techniques such as optimization, dynamic programming, numerical ... stochastic methods. We provide competitive total compensation packages, including base pay ...

Cellanome

Machine Learning Engineer

San Diego, CA · On-site

$160K - $215K/yr

Experience applying algorithmic techniques such as optimization, dynamic programming, numerical ... stochastic methods. We provide competitive total compensation packages, including base pay ...

ExxonMobil

Quant V&S Gas and Power

Spring, TX

... using stochastic, scenario based and optimization techniques. * Contribute optionality and ... dynamics. * Collaborate with quant modelling/technology/data teams to ensure robust model ...

ExxonMobil

Quant V&S Gas and Power

Spring, TX · On-site

... using stochastic, scenario based and optimization techniques. * Contribute optionality and ... dynamics. * Collaborate with quant modelling/technology/data teams to ensure robust model ...

ExxonMobil

Quant V&S Gas and Power

Spring, TX · On-site

... using stochastic, scenario based and optimization techniques. * Contribute optionality and ... dynamics. * Collaborate with quant modelling/technology/data teams to ensure robust model ...

Navstar

Senior Autonomy Engineer

Denver, CO · On-site

$150K - $260K/yr

MPC, trajectory optimization, dynamic programming, stochastic control, mixed integer programming, quadratic programming, etc. * ML/AI: reinforcement learning, imitation learning, transformer ...

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Dynamic Stochastic Optimization information

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$16K

$55.8K

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How much do dynamic stochastic optimization jobs pay per year?

As of Jun 5, 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 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 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 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 are the key skills and qualifications needed to thrive as a Dynamic Stochastic Optimization Specialist, and why are they important?

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.
Infographic showing various Dynamic Stochastic Optimization job openings in the United States as of May 2026, with employment types broken down into 2% Locum Tenens, and 98% Part Time. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.
Post doctoral researcher in Mathematics or Statistics

Post doctoral researcher in Mathematics or Statistics

University Of Maryland Baltimore County

Catonsville, MD • On-site

Full-time

Posted 14 days ago

Job description

Description The Department of Mathematics and Statistics at the University of Maryland, Baltimore County (UMBC) has an opening for a postdoctoral scholar position, starting in fall 2025, preferably with an interest or focus on "Applied Mathematics or Statistics, in particular relating to data science applications". The appointment is for a fixed term, but renewable upon satisfactory performance and funding availability. Candidates should have finished their Ph.D.

in applied mathematics, statistics, biostatistics, machine learning or a related field before their appointment start date. Successful candidates are expected to carry out research, collaborate with faculty members, apply for external funding, and teach courses. Qualifications Candidates in all areas of applied mathematics and statistics may apply.

Our interests include but are not limited to analysis and computation of partial differential equations and applications; stochastic processes and applications (e.g. mathematical biology, data science); mathematical biology with modeling and analysis of cellular dynamics (e.g. clustered cell migration, neuromechanical locomotion, network synchronization), parameter estimation (e.g.

in epidemiological spread, chemical reaction networks), emergent behavior (e.g. flocking, swarming); optimization theory and numerical optimization with applications to data science; high-dimensional statistics; Bayesian statistics; resampling techniques; digital twins; uncertainty quantification; statistical process control; foundations of machine learning and artificial intelligence; statistical applications to biomedical problems and precision medicine. Application Instructions Applicants should apply using: http://apply.interfolio.com/158844 Applicants should submit (a) a cover letter; (b) a curriculum vitae that includes publications; (c) a description of research interests and research plans; (d) a brief teaching statement; (e) a statement of commitment to inclusive excellence; and (e) have at least three letters of recommendation submitted on their behalf.

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