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Predictive Modeling Jobs in California (NOW HIRING)

Golden State

Data Scientist

San Francisco, CA · Remote

$165K/yr

In this role, you will make a positive impact on our research, predictive modeling, and long-term decision making to support our Basketball Operations stakeholders. Additionally, you will work ...

Golden State

Data Scientist

San Francisco, CA · Remote

$165K/yr

In this role, you will make a positive impact on our research, predictive modeling, and long-term decision making to support our Basketball Operations stakeholders. Additionally, you will work ...

Jobtailor

Data Scientist

San Francisco, CA · On-site

$140 - $210/hr

Build predictive models that matter: develop and deploy models for forecasting, segmentation, propensity scoring, and opportunity sizing across Cohere's core business lines. * Act like an owner: no ...

Hyundai Capital

Sr. Quantitative Modeler

Irvine, CA · Hybrid

Minimum 8 years predictive modeling experience with focus on credit risk, credit bureau data, regulatory requirements, market trends including 5 years within the financial and auto industry. * Master ...

LMI

Data Scientist - Clearance Required

Fort Bragg, CA · On-site

Develop, test, and refine predictive models to forecast resource consumption and annual rate projections with a maximum error margin of 1%. * Apply statistical analysis, feature engineering, time ...

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How much do predictive modeling jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for predictive modeling in California is $57.94, according to ZipRecruiter salary data. Most workers in this role earn between $51.97 and $67.36 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in predictive modeling, and why are they important?

To thrive in Predictive Modeling, you need strong statistical analysis, data mining, and machine learning skills, often supported by a degree in statistics, computer science, mathematics, or a related field. Expertise with tools such as Python, R, SAS, or SQL, as well as knowledge of data visualization software, is commonly required, and certifications in data science or analytics are a plus. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills for this role. Mastering these skills enables professionals to build accurate models, interpret data-driven results, and clearly communicate insights to stakeholders, which are critical for informed business decision-making.

What is predictive modeling?

A Predictive Modeling job involves using statistical techniques, machine learning algorithms, and data analysis to forecast future outcomes based on historical data. Professionals in this role build and test models to identify patterns, trends, and relationships in complex datasets. They commonly work in industries like finance, healthcare, and marketing to improve decision-making and optimize business processes. Strong skills in programming, data manipulation, and statistical analysis are essential for success in this role.

What does a typical workday look like for someone working in predictive modeling?

A typical day in predictive modeling involves gathering and cleaning data, selecting relevant features, and building statistical or machine learning models to forecast trends or behaviors. You’ll regularly use programming languages and analytics tools to test model performance and iterate on results, while documenting findings and preparing reports for internal teams or clients. Collaboration is often required with data engineers, subject matter experts, and business leaders to ensure that models align with organizational goals. Additionally, you may be tasked with presenting your insights to both technical and non-technical audiences, making strong communication skills essential for success in this role.

What are the most commonly searched types of Predictive Modeling jobs in California?

The most popular types of Predictive Modeling jobs in California are:

What are popular job titles related to Predictive Modeling jobs in California?

For Predictive Modeling jobs in California, the most frequently searched job titles are:

What job categories do people searching Predictive Modeling jobs in California look for?

The top searched job categories for Predictive Modeling jobs in California are:

What cities in California are hiring for Predictive Modeling jobs?

Cities in California with the most Predictive Modeling job openings:

Predictive Modeling jobs near you
Infographic showing various Predictive Modeling job openings in California as of August 2026, with employment types broken down into 77% Full Time, 19% Part Time, 2% Temporary, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $120,524 per year, or $57.9 per hour.

Device Modeling Engineer

Power Integrations

San Jose, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

The Device Modeling Engineer is responsible for the development, validation, and release of accurate device models and cells for silicon (Si) and wide-bandgap (WBG) power devices, supporting Power Integrations’ product development and technology roadmap.
This role is critical in bridging device physics, characterization, and circuit-level simulation to enable first-time-right silicon, robust product definition, and predictive design across multiple power platforms.
The ideal candidate brings deep expertise in semiconductor device physics, hands-on characterization, and model extraction, with a strong ability to collaborate across device, IC design, product engineering, and applications teams.

Key Responsibilities
Device Modeling & Model Development
•    Develop, maintain, and release device models and model libraries for Si and WBG (GaN) technologies across multiple voltage and power ranges
•    Create compact models suitable for circuit simulation (SPICE-level) and system-level design
•    Ensure models accurately capture static, dynamic, thermal, and transient behavior across operating conditions
•    Support development of next-generation GaN and high-voltage technologies through predictive modeling
Characterization & Parameter Extraction
•    Define and execute device characterization plans for model extraction
•    Perform electrical and thermal measurements, including switching behavior, loss mechanisms, and parasitic effects
•    Extract model parameters using measurement data and ensure correlation across: 
o    Process corners
o    Temperature and voltage extremes
o    System operating conditions
•    Drive improvements in measurement methodologies and test setups
Simulation & Validation
•    Perform device-level and circuit-level simulations to validate model accuracy
•    Correlate simulation vs. measured data and identify discrepancies
•    Work closely with IC design teams to ensure models are: 
o    Accurate for design
o    Efficient for simulation
o    Robust across use cases
•    Support validation for new product introductions (NPI) and technology releases
Technology & Product Support
•    Provide modeling support for new device architectures and process technologies
•    Evaluate electrical and thermal characteristics of GaN and high-voltage power devices
•    Support failure analysis, reliability studies, and qualification activities from a modeling perspective
•    Contribute to design reviews and risk assessments for new products
Cross-Functional Collaboration
•    Collaborate closely with: 
o    Device engineering
o    IC design and layout teams
o    Product and test engineering
o    Applications engineering
•    Ensure models meet internal design needs and external customer requirements
•    Support key customer engagements requiring model validation or customization
Model Infrastructure & Continuous Improvement
•    Maintain and enhance modeling flows, libraries, and documentation
•    Improve automation for parameter extraction, validation, and release processes
•    Drive best practices for model quality, version control, and deployment

Qualifications
Education & Experience
•    M.S. or Ph.D. in Electrical Engineering (semiconductor devices preferred)
•    Typical experience: 
o    Ph.D. + 3+ years, OR
o    M.S. + 6+ years, OR
o    B.S. + 8+ years
•    Proven track record in device modeling for Si and/or WBG technologies
Technical Skills
•    Deep understanding of: 
o    Semiconductor device physics (Si and GaN strongly preferred)
o    Device operation, parasitics, and switching behavior
•    Strong experience with: 
o    Model extraction and development
o    High-voltage device characterization and test systems 
o    CADENCE or equivalent simulation tools (Spectre/SPICE) 
•    Familiarity with: 
o    Compact modeling methodologies
o    Electro-thermal modeling
o    Behavioral modeling for system simulation