OR · On-site
... and stochastic optimization, auction theory and mechanism design, dynamic programming ... Proficiency in one of the following languages: Go, Java, C++ for production systems and Python for ...
... and stochastic optimization, auction theory and mechanism design, dynamic programming ... Proficiency in one of the following languages: Go, Java, C++ for production systems and Python for ...
... and stochastic optimization, auction theory and mechanism design, dynamic programming ... Proficiency in one of the following languages: Go, Java, C++ for production systems and Python for ...
... stochastic optimization) appropriate for a production healthcare environment where suboptimal actions have member impact. * Model member journey dynamics using tools from stochastic processes ...
... stochastic optimization) appropriate for a production healthcare environment where suboptimal actions have member impact. * Model member journey dynamics using tools from stochastic processes ...
You have applied stochastic optimization to problems in financial or electrical engineering ... and their dynamics. * You are experienced and comfortable developing and monitoring machine ...
You have applied stochastic optimization to problems in financial or electrical engineering ... and their dynamics. * You are experienced and comfortable developing and monitoring machine ...
Applied Scientist - Operations Research/Optimization, Sales Planning and Inventory Optimization S...
... stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming) and algorithms to design optimal or near optimal solution methodologies to be used by in-house ...
Applied Scientist - Operations Research/Optimization, Sales Planning and Inventory Optimization S...
... stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming) and algorithms to design optimal or near optimal solution methodologies to be used by in-house ...
Quantitative Researcher for Monetization
New York, NY · On-site
$150K - $180K/yr
You have applied stochastic optimization to problems in financial or electrical engineering ... and their dynamics. * You are experienced and comfortable developing and monitoring machine ...
Quantitative Researcher for Monetization
New York, NY · On-site
$150K - $180K/yr
You have applied stochastic optimization to problems in financial or electrical engineering ... and their dynamics. * You are experienced and comfortable developing and monitoring machine ...
Applied Scientist - Operations Research/Optimization, Sales Planning and Inventory Optimization S...
... stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming) and algorithms to design optimal or near optimal solution methodologies to be used by in-house ...
Applied Scientist - Operations Research/Optimization, Sales Planning and Inventory Optimization S...
... stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming) and algorithms to design optimal or near optimal solution methodologies to be used by in-house ...
... dynamics, and operational constraints with domain experts. * Develop RL agents using model-free ... and stochastic optimization to identify best-fit approaches. * Stay current with advances in ...
... dynamics, and operational constraints with domain experts. * Develop RL agents using model-free ... and stochastic optimization to identify best-fit approaches. * Stay current with advances in ...
STAFF ENGINEER, PHOTO DRAM
Boise, ID · On-site
Deep EUV knowledge and experience with CDU/overlay modeling, stochastic optimization, or defect ... Resilience and adaptability in a dynamic, evolving environment As a world leader in the ...
STAFF ENGINEER, PHOTO DRAM
Boise, ID · On-site
Deep EUV knowledge and experience with CDU/overlay modeling, stochastic optimization, or defect ... Resilience and adaptability in a dynamic, evolving environment As a world leader in the ...
... dynamics, and operational constraints with domain experts. * Develop RL agents using model-free ... and stochastic optimization to identify best-fit approaches. * Stay current with advances in ...
... dynamics, and operational constraints with domain experts. * Develop RL agents using model-free ... and stochastic optimization to identify best-fit approaches. * Stay current with advances in ...
Deep EUV knowledge and experience with CDU/overlay modeling, stochastic optimization, or defect ... Resilience and adaptability in a dynamic, evolving environment As a world leader in the ...
Deep EUV knowledge and experience with CDU/overlay modeling, stochastic optimization, or defect ... Resilience and adaptability in a dynamic, evolving environment As a world leader in the ...
... dynamics, and operational constraints with domain experts. * Develop RL agents using model-free ... and stochastic optimization to identify best-fit approaches. * Stay current with advances in ...
... dynamics, and operational constraints with domain experts. * Develop RL agents using model-free ... and stochastic optimization to identify best-fit approaches. * Stay current with advances in ...
Applied Scientist - Operations Research/Optimization, Sales Planning and Inventory Optimization S...
Seattle, WA · On-site
... stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming) and algorithms to design optimal or near optimal solution methodologies to be used by in-house ...
Applied Scientist - Operations Research/Optimization, Sales Planning and Inventory Optimization S...
Seattle, WA · On-site
... stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming) and algorithms to design optimal or near optimal solution methodologies to be used by in-house ...
... dynamics, c) helping to identify, recruit, train, and mentor members of our growing team of ... Experience with optimization techniques (e.g. stochastic optimization, robust optimization)
... dynamics, c) helping to identify, recruit, train, and mentor members of our growing team of ... Experience with optimization techniques (e.g. stochastic optimization, robust optimization)
Operations Analyst II
San Diego, CA · On-site
$73K - $81K/yr
... optimization techniques. * Assess and design production systems, facilities, supply chains ... programming, dynamic programming, queuing theory, stochastic models, and analytic hierarchy ...
Operations Analyst II
San Diego, CA · On-site
$73K - $81K/yr
... optimization techniques. * Assess and design production systems, facilities, supply chains ... programming, dynamic programming, queuing theory, stochastic models, and analytic hierarchy ...
Stochastic optimization tools to bridge between simulation and experiments. * Predict, measure and ... SPH), MD, BTE, Spectral Element, molecular dynamics, DSMC. * Thin film mechanics and ...
Stochastic optimization tools to bridge between simulation and experiments. * Predict, measure and ... SPH), MD, BTE, Spectral Element, molecular dynamics, DSMC. * Thin film mechanics and ...
Operations Analyst II
San Diego, CA · On-site
$73K - $81K/yr
... optimization techniques. * Assess and design production systems, facilities, supply chains ... programming, dynamic programming, queuing theory, stochastic models, and analytic hierarchy ...
Quick apply
Operations Analyst II
San Diego, CA · On-site
$73K - $81K/yr
... optimization techniques. * Assess and design production systems, facilities, supply chains ... programming, dynamic programming, queuing theory, stochastic models, and analytic hierarchy ...
... optimization techniques. * Assess and design production systems, facilities, supply chains ... programming, dynamic programming, queuing theory, stochastic models, and analytic hierarchy ...
... optimization techniques. * Assess and design production systems, facilities, supply chains ... programming, dynamic programming, queuing theory, stochastic models, and analytic hierarchy ...
Stochastic optimization tools to bridge between simulation and experiments. * Predict, measure and ... SPH), MD, BTE, Spectral Element, molecular dynamics, DSMC. * Thin film mechanics and ...
Stochastic optimization tools to bridge between simulation and experiments. * Predict, measure and ... SPH), MD, BTE, Spectral Element, molecular dynamics, DSMC. * Thin film mechanics and ...
OR · On-site
... stochastic optimization (Gurobi, CPLEX, OR-Tools, Pyomo). * Working knowledge of SAP / ECC / S ... Why Game Plan Tech? Join a dynamic and growing team at Game Plan Tech, dedicated to empowering ...
OR · On-site
... stochastic optimization (Gurobi, CPLEX, OR-Tools, Pyomo). * Working knowledge of SAP / ECC / S ... Why Game Plan Tech? Join a dynamic and growing team at Game Plan Tech, dedicated to empowering ...
Dynamic Stochastic Optimization information
See salary details
$16K - $23.8K
3% of jobs
$23.8K - $31.6K
6% of jobs
$35.1K is the 25th percentile. Wages below this are outliers.
$31.6K - $39.5K
34% of jobs
$39.5K - $47.3K
2% of jobs
The median wage is $50K / yr.
$47.3K - $55.1K
11% of jobs
$55.1K - $62.9K
14% of jobs
$67.1K is the 75th percentile. Wages above this are outliers.
$62.9K - $70.7K
8% of jobs
$70.7K - $78.5K
5% of jobs
$78.5K - $86.4K
13% of jobs
$86.4K - $94.2K
1% of jobs
$94.2K - $102K
2% of jobs
$16K
$55.8K
$102K
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?
| Aspect | Dynamic Stochastic Optimization | Data Analyst |
|---|---|---|
| Required Credentials | Advanced degrees in Operations Research, Mathematics, or related fields | Bachelor's or Master's in Data Science, Statistics, or related fields |
| Work Environment | Quantitative teams, research labs, or analytics departments | Business units, marketing, finance, or operations teams |
| Industry Usage | Supply chain, finance, energy, and logistics | Marketing, finance, healthcare, and retail sectors |
| Search & Comparison Intent | Understanding optimization techniques for decision-making under uncertainty | Analyzing 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.
Instacart rating
6.7
Based on 29 frontline employees who took The Breakroom Quiz
Job description
Overview
The Advertiser Optimization team is the decision-making engine of Instacart's $1B+ ads business. We own the systems responsible for Bidding, Pacing, Budgeting, and Targeting: converting stated advertiser goals into real-time auction actions. Our mission is to maximize realized Advertiser Value by deciding when to participate, how much to bid, and how fast to spend, all while balancing User Experience and Platform Revenue.
We are hiring a Senior Applied Scientist II to lead the algorithmic direction of these systems. This is a role for someone who thinks in terms of control theory, constrained optimization, and auction economics, and who can translate those frameworks into production code that makes millions of decisions per day. You will formulate problems from first principles, shape the technical roadmap, and own systems end-to-end from mathematical design through production deployment through impact measurement.
About the Job- Design and evolve real-time bid optimization systems that translate advertiser goals (target ROAS, budget constraints) into optimal auction bids under uncertainty. Formulate the bidding problem as constrained optimization and build the feedback mechanisms that keep bids aligned with realized outcomes.
- Build intelligent budget pacing algorithms that distribute spend across time and auction opportunities. The core challenge: allocating a finite daily budget across stochastic demand while maximizing total value, subject to advertiser constraints and time-varying conversion dynamics.
- Develop the analytical frameworks that connect bidding, pacing, and budgeting into a coherent optimization objective.
- Shape auction mechanics including reserve pricing, multi-slot allocation, and bid-to-price mapping. Reason about mechanism design tradeoffs between advertiser outcomes, platform revenue, and marketplace efficiency.
- Own the full research-to-production loop: diagnose system behavior from large-scale data, formulate hypotheses, design experiments, ship production code, and measure impact. Write technical strategy documents that set the algorithmic direction for the team.
- MS or PhD in operations research, applied mathematics, control systems, computational economics, or a related quantitative field.
- 8+ years of experience building and deploying optimization or control systems in production environments (not just research prototypes).
- Strong foundation in at least two of: feedback control theory (PID, MPC), convex and stochastic optimization, auction theory and mechanism design, dynamic programming.
- Proficiency in one of the following languages: Go, Java, C++ for production systems and Python for data analysis and offline pipelines.
- Demonstrated ability to translate mathematical formulations into production code that runs at scale (millions of decisions per day, sub-100ms latency constraints).
- Experience with real-time bidding systems, ad auction optimization, or computational advertising at scale.
- Background in budget-constrained allocation methods. Experience with adaptive control or model-predictive control in production systems.
- Familiarity with causal inference and experimental design for evaluating algorithmic changes in marketplace settings.
- Track record of shaping technical strategy and driving cross-functional alignment between engineering, product, and data science.
What Instacart employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Instacart
Sourced by ZipRecruiter
Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.
Industry
Technology, communication and media
Company size
10,000+ Employees
Headquarters location
San Francisco, CA, US
Year founded
2012