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Applied Mathematics Phd Jobs in Riverside, CA (NOW HIRING)

Advanced degree (MS or PhD) in Operations Research, Applied Mathematics, Computer Science, or related field. Preferred Qualifications: * Experience with store allocation and replenishment systems.

Engineer II, Algorithm

Irvine, CA ยท On-site

$120K - $150K/yr

Bachelor's degree in Electrical Engineering, Biomedical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field required. Master's or PhD ...

Bachelor's degree in Electrical Engineering, Biomedical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field required. Master's or PhD ...

Apply control engineering, scientific, mathematical, signal processing, and human physiology ... Or a PhD or equivalent in an Engineering or Scientific field with a minimum of 8 years of ...

Applied Mathematics Phd information

See Riverside, CA salary details

$23.5K

$61.4K

$98.6K

How much do applied mathematics phd jobs pay per year?

As of Aug 22, 2026, the average yearly pay for applied mathematics phd in Riverside, CA is $61,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,900.00 and $73,000.00 per year, depending on experience, location, and employer.

What is an applied mathematics PhD?

Applied Mathematics PhDs are advanced academic degrees focused on the development and application of mathematical methods to solve real-world problems in science, engineering, business, and other fields. Students in these programs engage in research that often bridges theoretical mathematics and practical applications, such as modeling physical phenomena, analyzing data, or optimizing systems. Graduates are equipped to work in academia, industry, government, or research institutions, contributing mathematical expertise to a wide range of disciplines.

What types of projects or research areas do applied mathematics PhDs typically work on within industry settings?

Applied Mathematics PhD holders often work on projects involving data analysis, mathematical modeling, algorithm development, and optimization in industries such as finance, technology, healthcare, and engineering. They may collaborate with interdisciplinary teams to solve complex real-world problems, such as developing predictive models, optimizing processes, or designing simulations. These roles often require strong communication skills to translate mathematical concepts into practical solutions for stakeholders. The work environment is typically collaborative, with opportunities to lead projects or move into specialized or managerial positions over time.

What are the key skills and qualifications needed to thrive as an applied mathematics PhD, and why are they important?

To thrive as an Applied Mathematics PhD, you need advanced mathematical modeling, analytical thinking, and quantitative problem-solving skills, typically supported by a doctoral degree in mathematics or a related field. Familiarity with programming languages (such as Python, MATLAB, or R), statistical software, and experience with computational tools is often required. Strong communication, collaboration abilities, and adaptability are essential soft skills for conveying complex concepts and working in multidisciplinary teams. These skills are crucial for developing innovative solutions to real-world problems and effectively contributing to academic, industrial, or research environments.

What is the difference between Applied Mathematics Phd vs Data Scientist?

AspectApplied Mathematics PhdData Scientist
Required CredentialsPhD in Applied Mathematics or related fieldBachelor's or Master's in Computer Science, Statistics, or related field; some roles prefer PhD
Work EnvironmentResearch labs, academia, industry R&DTech companies, finance, healthcare, consulting
Industry UsageModel development, algorithm design, researchData analysis, predictive modeling, business insights
Common Search/ComparisonApplied Mathematics Phd vs Data Scientist

While both roles involve data analysis and modeling, Applied Mathematics Phds focus more on theoretical research and developing new algorithms, often in research or academic settings. Data Scientists typically apply existing models to solve business problems in industry. The roles overlap in quantitative skills but differ in focus and work environment.

Are applied mathematics PhDs in demand?

Applied mathematics PhDs are in demand across industries such as finance, data science, engineering, and research, where advanced analytical and problem-solving skills are valued. These roles often require strong programming, statistical, and modeling expertise, with employment opportunities available in academia, government, and private sectors.

Is an applied mathematics PhD worth it?

An applied mathematics PhD can lead to careers in research, data analysis, finance, and academia, often requiring strong analytical and programming skills. While it offers advanced expertise, the value depends on career goals and industry demand, which can vary by field and location.

What can I do with a PhD in applied mathematics?

A PhD in applied mathematics prepares individuals for research, data analysis, and modeling roles across industries such as finance, engineering, technology, and academia. Graduates often work as quantitative analysts, data scientists, operations researchers, or in roles requiring advanced problem-solving and programming skills with tools like MATLAB, Python, or R.

What are popular job titles related to Applied Mathematics Phd jobs in Riverside, CA?

For Applied Mathematics Phd jobs in Riverside, CA, the most frequently searched job titles are:

What job categories do people searching Applied Mathematics Phd jobs in Riverside, CA look for?

The top searched job categories for Applied Mathematics Phd jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Applied Mathematics Phd jobs?

Cities near Riverside, CA with the most Applied Mathematics Phd job openings:

Infographic showing various Applied Mathematics Phd job openings in Riverside, CA as of August 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 100% In-person job distribution, with an average salary of $61,383 per year, or $29.5 per hour.

Senior Data Scientist

Prodapt

Irvine, CA โ€ข On-site

Other

Posted 27 days ago


Job description

We are seeking a highly skilled Data Scientist with expertise in demand forecasting, supply chain optimization, and retail inventory management. In this role, you will develop, retrain, and validate demand forecasting models tailored to multiple regional markets, while collaborating closely with the optimization team to enhance inventory allocation and replenishment strategies. You will work with large-scale retail datasets, deploy models using AWS SageMaker, and operate within a federated data architecture to ensure accurate, scalable forecasting solutions.

Key Responsibilities:

  • Develop, retrain, and adapt demand forecasting models (ARIMA, Prophet, neural networks) to reflect regional seasonality, buying patterns, and lead times.
  • Calibrate and validate forecast accuracy using federated regional data to meet go-live thresholds before market activations.
  • Collaborate with the supply chain optimization team to provide inputs for inventory allocation and replenishment engines.
  • Translate complex business constraints into mathematical optimization models using linear programming and constraint satisfaction techniques.
  • Design and implement optimization solutions for retail inventory allocation and replenishment using Python libraries (PuLP, OR-Tools) and solvers (Gurobi, CPLEX).
  • Deploy and maintain forecasting and optimization models on AWS SageMaker, integrating with Lambda and other AWS services for scalable workflows.
  • Work independently with architectural guidance from lead scientists, and mentor junior applied scientists as needed.
  • Communicate model insights and business impact effectively to cross-functional teams.

Required Qualifications:

  • Strong experience in time series forecasting methods such as ARIMA, Prophet, and neural forecasting models (LSTM, RNN).
  • Proficiency in mathematical optimization techniques including linear programming, constraint satisfaction, and multi-objective optimization.
  • Hands-on experience with Python and relevant libraries: pandas, numpy, scikit-learn, statsmodels, PuLP, OR-Tools.
  • Familiarity with optimization solvers such as Gurobi or CPLEX.
  • Experience working with large-scale retail datasets and federated data architectures.
  • Expertise in retail demand planning, demand sensing, and supply chain or inventory management.
  • Proficient in AWS ML stack, especially SageMaker for model training and deployment, and Lambda for serverless integration.
  • Strong SQL skills for data extraction and manipulation.
  • Ability to translate business requirements into mathematical and computational models.
  • Excellent problem-solving skills and ability to work independently.
  • Experience mentoring or leading applied scientists is a plus.
  • Advanced degree (MS or PhD) in Operations Research, Applied Mathematics, Computer Science, or related field.

Preferred Qualifications:

  • Experience with store allocation and replenishment systems.
  • Familiarity with agentic AI frameworks or advanced AI-driven decision-making systems.
  • Knowledge of CI/CD pipelines for ML model deployment.
  • Multi-market or international retail exposure.