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Statistical Modeling Jobs in California (NOW HIRING)

YO AI Labs

Data Scientist

Glendale, CA

Python Machine Learning, data science, AWS, Statistical Modeling, Semantic Search, Vector DB, GenAI, SQL Technical Responsibilities : * Design and Execute Experiments: Lead end-to-end A/B testing ...

Ignite Digital

Mid Data Scientist

San Diego, CA

In this role, you will leverage advanced analytics, machine learning, and statistical modeling techniques to extract insights from complex datasets. You will work closely with cross-functional teams ...

Compunnel

Senior Data Scientist

Glendale, CA · On-site

The ideal candidate will have strong expertise in applied machine learning, statistical modeling, MLOps, and cloud-native technologies, with the ability to develop scalable AI solutions and ...

Fabergent

Sr Data Scientist

San Ramon, CA

Advanced degree in Applied Statistics, Economics, Computer Science, or Operations Research (Master's degree required). 1+ years experience in advanced analytics, model building, statistical modeling ...

Apple

Senior Apps Applied Scientist

Cupertino, CA · On-site +1

$184K - $324K/yr

The Applications team is looking for an outstanding Applied Scientist who will strengthen our team's capabilities in statistical modeling, machine learning, and foundational AI development. This role ...

Apple

Senior Apps Applied Scientist

Cupertino, CA · On-site +1

$184K - $324K/yr

The Applications team is looking for an outstanding Applied Scientist who will strengthen our team's capabilities in statistical modeling, machine learning, and foundational AI development. This role ...

Apple

Senior Apps Applied Scientist

Cupertino, CA · On-site +1

$184K - $324K/yr

The Applications team is looking for an outstanding Applied Scientist who will strengthen our team's capabilities in statistical modeling, machine learning, and foundational AI development. This role ...

Mytra

Senior Modeling & Optimization Engineer

Brisbane, CA · On-site

$125K - $172K/yr

... statistical modeling, or applied data science. • Ability to design experiments, analyze data, and communicate insights clearly to technical and non-technical audiences. • Solid engineering ...

NextDeavor Inc.

Data Scientist

San Francisco, CA

$90.14 - $112.68/hr

Apply quantitative analysis and statistical modeling to uncover customer behavior and trends * Act as a thought partner to business leads and influence decisions through data-driven storytelling

Panasonic

Data Scientist III

Irvine, CA · On-site

Modeling & Applied Statistics Build out predictive Machine Learning (ML) modeling using R and Python that harnesses customer and competitive analysis data to spot emerging trends and areas of ...

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All JobsStatistical Modeling JobsStatistical Modeling Jobs in California

Statistical Modeling information

See California salary details

$36K

$54.6K

$97.7K

How much do statistical modeling jobs pay per year?

As of Jul 24, 2026, the average yearly pay for statistical modeling in California is $54,625.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,400.00 and $59,200.00 per year, depending on experience, location, and employer.

How much do data modelers make?

Data modelers, also known as statistical modelers, typically earn between $70,000 and $120,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in machine learning or programming may earn higher salaries, especially in tech hubs or large organizations.

Are statisticians highly paid?

Statisticians are generally well-paid, with median salaries often above the national average, especially for those with advanced skills in statistical software, programming, and data analysis. Salaries vary based on experience, education, industry, and location, but the profession is considered financially rewarding compared to many other roles in data analysis and modeling.

What are some common challenges faced by professionals in statistical modeling roles, and how can they be managed?

Professionals in statistical modeling often encounter challenges such as dealing with incomplete or messy data, selecting the most appropriate modeling techniques, and clearly communicating complex results to non-technical stakeholders. Managing these challenges typically involves collaborating closely with data engineers and domain experts, employing robust data cleaning practices, and staying up-to-date with new statistical methods. Additionally, effective communication skills are essential for translating technical findings into actionable business insights, ensuring that modeling efforts drive real-world impact.

What do statistical models do?

Statistical modeling involves creating mathematical representations of data to analyze relationships, make predictions, and inform decision-making. Professionals in this field use tools like regression analysis and statistical software to interpret complex data sets and support evidence-based conclusions.

What is statistical modeling?

Statistical modeling is the process of using mathematical models and statistical techniques to analyze data, identify patterns, and make predictions or inferences. It involves building models that represent relationships between variables in real-world systems. These models can be used for forecasting, hypothesis testing, and decision-making in various fields such as business, science, and engineering. Statistical modeling helps turn raw data into actionable insights by quantifying uncertainty and highlighting significant trends.

What are the key skills and qualifications needed to thrive as a Statistical Modeler, and why are they important?

To excel as a Statistical Modeler, a solid background in statistics, mathematics, and data analysis—often supported by a degree in a quantitative field—is essential. Proficiency with statistical software such as R, Python, SAS, or SPSS and familiarity with data visualization tools are typically required. Strong problem-solving skills, critical thinking, and effective communication help convey complex findings to non-technical stakeholders. These skills ensure accurate model development, actionable insights, and effective decision-making based on data.

What is the difference between Statistical Modeling vs Data Analyst?

AspectStatistical ModelingData Analyst
Required CredentialsDegree in statistics, mathematics, or related field; proficiency in statistical softwareDegree in data science, statistics, or related; strong analytical skills
Work EnvironmentResearch, academia, or data-driven industries; focus on model developmentBusiness, marketing, or finance; focus on data interpretation and reporting
Employer & Industry UsageUsed in industries requiring predictive models and complex analysisUsed across various industries for data reporting and insights

Statistical Modeling involves creating mathematical models to understand data patterns and make predictions, often requiring advanced statistical knowledge. Data Analysts focus on interpreting data, generating reports, and providing actionable insights. While both roles work with data, Statistical Modeling emphasizes model development, whereas Data Analysts concentrate on data interpretation and presentation.

Is AI replacing statisticians?

Statisticians play a key role in designing experiments, analyzing data, and interpreting results, and AI tools are used to enhance these tasks rather than replace the profession. AI can automate routine data processing, but statisticians are needed for complex modeling, decision-making, and ensuring data quality. Proficiency in statistical software and programming languages like R or Python remains essential for the job.
What are popular job titles related to Statistical Modeling jobs in California? For Statistical Modeling jobs in California, the most frequently searched job titles are:
What job categories do people searching Statistical Modeling jobs in California look for? The top searched job categories for Statistical Modeling jobs in California are:
What cities in California are hiring for Statistical Modeling jobs? Cities in California with the most Statistical Modeling job openings:
Statistical Modeling jobs near you
Infographic showing various Statistical Modeling job openings in California as of July 2026, with employment types broken down into 68% Full Time, 13% Part Time, and 19% Contract. Highlights an 67% Physical, 3% Hybrid, and 30% Remote job distribution, with an average salary of $54,625 per year, or $26.3 per hour.
Senior Architecture Energy Modeling Engineer

Senior Architecture Energy Modeling Engineer

NVIDIA

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Posted 22 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

5th of 217 rated software companies

Job description

Job Summary:
NVIDIA is a leader in energy-efficient products, and they are seeking a Senior Architecture Energy Modeling Engineer. The role involves researching, developing, and deploying methodologies to enhance the energy efficiency of NVIDIA's products, particularly through the development of Machine Learning based power models for GPUs.
Responsibilities:
• Work with architects, designers, and performance engineers to develop an energy-efficient GPU.
• Identify key design features and workloads for building Machine Learning based unit power/energy models.
• Develop and own methodologies and workflows to train models using ML and/or statistical techniques.
• Improve the accuracy of trained models by using different model representations, objective functions, and learning algorithms.
• Develop methodologies to estimate data movement power/energy accurately.
• Correlate the predicted energy from models built at different stages of the design cycle, with the goal of bridging early estimates to silicon.
• Work with performance infrastructure teams to integrate power/energy models into their platforms to enable combined reporting of performance and power for various workloads.
• Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL, and architectural simulators. Identify and suggest solutions to fix the energy inefficiencies.
• Prototype new architectural features, build an energy model for those new features, and analyze the system impact.
• Identify, suggest, and/or participate in studies for improving GPU perf/watt.
Qualifications:
Required:
• MS (or equivalent experience) with proven experience or PhD in related fields.
• 6+ years of experience.
• Strong coding skills, preferably in Python, C++.
• Background in machine learning, AI, and/or statistical modeling.
• Background in computer architecture and interest in energy-efficient GPU designs.
• Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.
• Basic understanding of fundamental concepts of energy consumption, estimation, and low power design.
• Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.
• Good verbal/written communication and interpersonal skills.
Preferred:
• Familiarity with Verilog and ASIC design principles is a plus.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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