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Mathematical Optimization Jobs in California (NOW HIRING)

SEO Analyst

La Mirada, CA · On-site

$81K - $108K/yr

Position Summary The SEO Analyst will be primarily focused on reporting, analytics, and technical ... S.) or equivalent from four-year college in business, mathematics, technical field, or related ...

We will do this primarily by building software and mathematical optimization models, not manual spreadsheets.This role is very cross-functional and provides an opportunity to work with supply chain ...

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Mathematical Optimization information

See California salary details

$15.8K

$55.1K

$100.7K

How much do mathematical optimization jobs pay per year?

As of Jul 16, 2026, the average yearly pay for mathematical optimization in California is $55,064.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,500.00 and $71,600.00 per year, depending on experience, location, and employer.

What is a Mathematical Optimization job?

A Mathematical Optimization job involves using mathematical techniques and algorithms to find the best possible solution to a given problem while satisfying constraints. Professionals in this field work in industries like finance, logistics, engineering, and artificial intelligence to optimize processes, minimize costs, or maximize efficiency. They use tools like linear programming, integer programming, and machine learning to solve complex decision-making problems.

What are some typical projects or problems tackled by professionals in Mathematical Optimization?

Professionals in Mathematical Optimization often work on projects involving resource allocation, supply chain management, scheduling, logistics, network design, or financial portfolio optimization. They use mathematical models to define and solve problems where the objective is to maximize efficiency or minimize costs under various constraints. Work may include collaborating with cross-functional teams to gather requirements, analyze large datasets, develop optimization algorithms, and implement solutions within existing business systems. These roles are found across industries such as manufacturing, transportation, finance, and technology, providing diverse and challenging opportunities. This variety in project scope allows for continuous learning and professional growth.

What are the key skills and qualifications needed to thrive in the Mathematical Optimization position, and why are they important?

To thrive in Mathematical Optimization, you need a strong background in mathematics, statistical modeling, and algorithm development, often supported by a degree in mathematics, operations research, engineering, or related fields. Proficiency with programming languages such as Python, MATLAB, or specialized optimization software (like Gurobi, CPLEX, or AMPL) is typically required. Strong analytical thinking, problem-solving skills, and the ability to communicate complex concepts clearly are critical soft skills for this role. These skills enable professionals to design effective solutions, interpret results, and convey recommendations to both technical and non-technical stakeholders.

What are the most commonly searched types of Mathematical Optimization jobs in California? The most popular types of Mathematical Optimization jobs in California are:
What cities in California are hiring for Mathematical Optimization jobs? Cities in California with the most Mathematical Optimization job openings:
Senior AI Scientist - Planning

Senior AI Scientist - Planning

Avathon

Pleasanton, CA

Full-time

Medical, Retirement

Re-posted 15 days ago


Job description

Who We Are & Why Join Us

Avathon is the leading Industrial AI autonomy platform, helping customers across heavy industries -- energy, mining, manufacturing, aerospace, defense, and logistics -- accelerate the journey toward autonomous operations. Our platform is built on a Computational Knowledge Graph foundation that contextualizes and connects operational data across siloed systems, bringing together time series, structured, unstructured, and machine vision data to power AI-driven applications in asset performance management, supply chain intelligence, visual AI, and global trade management. With capabilities spanning digital twins, normal behavior modeling, natural language processing, and computer vision, Avathon delivers real-time predictive intelligence and agentic decision-making at industrial scale.

Cutting-Edge AI Innovation -- Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. High-Growth Environment -- Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm. Meaningful Impact -- Work on AI-driven projects that drive real change across industries and improve lives.

Learn more at: avathon.com


About the Role

As a Senior AI Scientist – Planning, you will design and develop the AI and optimization models that power Avathon's planning intelligence - demand forecasting, supply planning, inventory optimization, and S&OP decision support for customers across energy, mining, manufacturing, and logistics.

This role sits at the intersection of AI, ML and operations research. You will build models that work with complex supply chain data - demand history, ERP/MRP transactions, and commercial forecasts across multi-echelon networks with long lead times and constrained capacity. The work is equal parts applied research and production delivery. You will develop novel approaches where standard methods fall short and ship them into a platform used by enterprise customers. You will report into the Data Science org and work closely with product and engineering.

You Will

  • Build demand forecasting models across industrial verticals, applying probabilistic, hierarchical, and intermittent demand methods where history is short or volatile
  • Design supply planning and inventory optimization models across multi-echelon networks with capacity constraints and variable lead times
  • Formulate and solve optimization problems (MIP, LP, constraint programming) for production scheduling, allocation, and resource planning
  • Build simulation and scenario analysis frameworks to support S&OP and integrated business planning workflows
  • Define evaluation metrics, build backtesting pipelines, and run controlled experiments to measure and improve model performance
  • Integrate cross-domain signals from Avathon's Computational Knowledge Graph -- asset health, logistics, procurement - into planning models
  • Own the path from research to production in collaboration with ML Engineering, delivering scalable and monitored services
  • Mentor junior data scientists on technical depth and OR/ML fundamentals

You'll Have

  • Ph.D. or master's degree in operations research, Industrial Engineering, Statistics, Computer Science, Applied Mathematics, or a related quantitative field
  • 10-15 years of industry experience in applied ML, optimization, or Supply Chain planning systems
  • Deep experience in at least two of: demand forecasting, supply/inventory optimization, production scheduling, or S&OP analytics
  • Proficiency in Python with hands-on experience in optimization solvers (Gurobi, CPLEX, OR-Tools, or similar) or forecasting libraries (Prophet, statsmodels, GluonTS, or similar)
  • Strong foundation in statistical modeling with sound judgment on when simple methods outperform complex ones
  • Experience with supply chain and operational data - demand history, ERP/MRP transactions, and planning system outputs
  • Ability to translate business problems into mathematical optimization or ML formulations
  • Experience deploying models into production environments

Preferred Qualifications

  • Ph.D. in Operations Research, Industrial Engineering, Statistics, or a related field
  • Background in supply chain planning platforms or industrial AI (o9, Blue Yonder, Kinaxis, or similar), preferably within the supply chain industry
  • Experience in supply chain planning platforms or industrial AI (o9 Solutions, Blue Yonder, Kinaxis, or similar) preferably from Supply Chain industry.
  • Experience with multi-echelon inventory optimization or network design
  • Familiarity with probabilistic programming or Bayesian methods for demand sensing
  • Experience with cloud ML infrastructure (AWS SageMaker, GCP Vertex, or equivalent)
  • Domain experience in energy, mining, manufacturing, aerospace, or logistics or Track record of publishing or presenting applied OR/ML work as plus

Interview Process

As part of the interview process, you will be asked to complete a technical assessment.

Benefits & Perks

What are the benefits and perks at Avathon? Below are some highlights we offer to our U.S. full-time employees -- we'd love to connect and share more!

  • Evolving culture with the opportunity to drive new ideas and technology
  • Stock Option Grants
  • Medical Coverage and Parental Leave Plans
  • 401k with Employer Match
  • Monthly Technology Allowance
  • Newly renovated office space located near Pleasanton, CA -- including fully stocked beverage and snack areas

Contract and temporary roles are not eligible for the above benefits.

Compensation

Pay Range: $160k - $240k salary annually. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.

Location: This role is not remote. Candidates must be based in the Bay Area, CA and are expected to report to our Pleasanton office 5 days a week.

Avathon is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.

Avathon is committed to providing reasonable accommodations throughout the recruiting process. If you need a reasonable accommodation, please contact us to discuss how we can assist you.