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Applied Mathematics Computer Science Jobs in Irvine, CA

Prodapt

Senior Data Scientist

Irvine, CA · On-site

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

Hireblazer

Senior Data Scientist

Irvine, CA · On-site

D. degree in Computer Science, Applied Mathematics, (Bio) Statistics, Applied Statistics, Economics, or similar quantitative fields. Experience developing and deploying models related to recommender ...

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Applied Mathematics Computer Science information

What is the difference between Applied Mathematics Computer Science vs Data Analyst?

AspectApplied Mathematics Computer ScienceData Analyst
Required CredentialsBachelor's or higher in applied math, computer science, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentResearch labs, tech companies, academiaBusiness, finance, healthcare, and marketing sectors
Employer & Industry UsageTech firms, research institutions, universitiesCorporations, consulting firms, government agencies
Common Search & ComparisonApplied Mathematics Computer Science vs Data Analyst

Applied Mathematics Computer Science focuses on developing algorithms, modeling, and computational techniques, often requiring programming and mathematical skills. Data Analysts interpret data to provide insights, primarily using statistical tools. While both roles involve data and programming, Applied Mathematics Computer Science emphasizes algorithm development and complex modeling, whereas Data Analysts focus on data interpretation and reporting.

Is applied mathematics related to computer science?

Applied mathematics is closely related to computer science, as it provides foundational concepts such as algorithms, data analysis, and modeling that are essential in computing. Many computer science roles, including those in software development and data science, require strong mathematical skills and knowledge of mathematical tools like linear algebra and calculus.

What can I do with a degree in applied mathematics and computer science?

A degree in applied mathematics and computer science prepares individuals for roles such as data analyst, software developer, quantitative analyst, or systems engineer. These positions often require strong problem-solving skills, programming knowledge, and familiarity with tools like Python, R, or MATLAB, and may involve working in industries such as finance, technology, or research.

What can you do with a BS in applied mathematics computer science?

A BS in applied mathematics and computer science prepares graduates for roles such as data analyst, software developer, quantitative analyst, or systems analyst. These positions often require skills in programming, statistical analysis, and problem-solving, and may involve working with tools like Python, R, or SQL in various industries including finance, technology, and engineering.

What are popular job titles related to Applied Mathematics Computer Science jobs in Irvine, CA?

For Applied Mathematics Computer Science jobs in Irvine, CA, the most frequently searched job titles are:

What job categories do people searching Applied Mathematics Computer Science jobs in Irvine, CA look for?

The top searched job categories for Applied Mathematics Computer Science jobs in Irvine, CA are:

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Applied Mathematics Computer Science jobs near you

Senior Data Scientist

Prodapt

Irvine, CA • On-site

Other

This job post has expired 3 days ago. Applications are no longer accepted.

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.

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