ZipRecruiter

Log In

1

Statistical Modeling Jobs in California (NOW HIRING)

Experian

Senior Data Modeling Analyst - Remote

Costa Mesa, CA · On-site +1

$92K - $116K/yr

Build statistical and machine learning models through all phases of development, from design through training, evaluation, validation and implementation * Use a broad set of technologies: SQL ...

Experian

Senior Data Modeling Analyst - Remote

Costa Mesa, CA · On-site +1

$92K - $116K/yr

Build statistical and machine learning models through all phases of development, from design through training, evaluation, validation and implementation * Use a broad set of technologies: SQL ...

Ra

Marketing Analytics Manager

Sacramento, CA

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

Ra

Marketing Analytics Manager

El Segundo, CA · On-site

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

Ra

Marketing Analytics Senior Manager

San Jose, CA

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

Ra

Marketing Analytics Senior Manager

Orange, CA

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

Ra

Marketing Analytics Manager

San Francisco, CA

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

Ra

Marketing Analytics Manager

Orange, CA · On-site

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

Ra

Marketing Analytics Manager

Los Angeles, CA

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

Ra

Marketing Analytics Manager

San Diego, CA

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

Ra

Marketing Analytics Manager

San Jose, CA · On-site

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

next page

Showing results 1-20

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 1, 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 June 2026, with employment types broken down into 94% Full Time, 5% Part Time, and 1% Temporary. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $54,625 per year, or $26.3 per hour.
Adjunct Instructor in Statistical Modeling and Causal Inference

Adjunct Instructor in Statistical Modeling and Causal Inference

Brandeis University

Brandeis, CA • On-site

$6.5K/mo

Part-time

Posted 2 days ago

Job description

Brandeis University's Online Applied Data Science and Decision Analytics Program is seeking an Adjunct Faculty member for RADS 105 Statistical Modeling and Causal Inference for the Fall 1 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Applied Data Science and Decision Analytics.

This course will cover regression, identification strategies, and causal inference techniques for evaluation of programs, products, and policies.

Core Course Responsibilities Summary:

  • Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.

  • Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.

  • Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.

  • Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.

Qualifications:

  • Required:

    • Advanced degree (MS or Ph.D.) in Statistics, Biostatistics, Applied Mathematics,Data Science or a related field.

    • Experience in statistical modeling and causal inference, including regression analysis, identification strategies, and methods for addressing bias and confounding in observational data. Ability to apply models to real-world program, product, or policy evaluation contexts.

    • Professional experience building regression, generalized linear models, hierarchical/multilevel models, and Bayesian approaches

    • The ability to apply models to realworld datasets and to incorporate statistical software such as SPSS.

    • At least 1 year of teaching or training experience (preferably online/asynchronous)

    • Experience with online instruction

    • Excellent communication and teaching skills in an online learning environment.

  • Preferred:

    • Prior online teaching experience at the graduate level

    • Knowledge of global learner personas and culturally responsive pedagogy

    • Familiarity with Moodle LMS and digital authoring tools (e.g., H5P)

Interested candidates should submit:

A cover letter highlighting relevant qualifications and teaching experience.

A current CV or resume.

Contact information for three professional references.

Application review begins May 27, 2026 though we will continue to accept submissions on an ongoing basis.

This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.

Compensation for this position is $6573.15

Pay Range Disclosure

The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.

Equal Opportunity Statement

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").

Apply