ZipRecruiter

Log In

1

Statistical Engineer Jobs in California (NOW HIRING)

next page

Showing results 1-20

All JobsStatistical Engineer JobsStatistical Engineer Jobs in California

Statistical Engineer information

See California salary details

$32.6K

$92.8K

$143.6K

How much do statistical engineer jobs pay per year?

As of Jun 21, 2026, the average yearly pay for statistical engineer in California is $92,798.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,500.00 and $107,100.00 per year, depending on experience, location, and employer.

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

To thrive as a Statistical Engineer, you need strong skills in statistical analysis, mathematics, and data interpretation, usually backed by a degree in statistics, engineering, or a related field. Familiarity with statistical software (such as R, SAS, or Python), data visualization tools, and knowledge of quality control systems are typically required. Critical thinking, problem-solving, and effective communication are essential soft skills for translating data insights into actionable solutions. These skills ensure accurate data-driven decision-making and process optimization, which are vital for organizational success.

What engineers make $300,000 a year?

Senior engineers in specialized fields such as petroleum, software, or aerospace engineering can earn $300,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often involves working in high-demand industries, holding advanced degrees, or obtaining professional certifications.

What are Statistical Engineers?

Statistical Engineers are professionals who apply statistical methods and techniques to solve engineering and production-related problems. They analyze data, design experiments, and develop models to optimize processes, improve product quality, and support decision-making in various industries. Their work often involves collaborating with engineers, scientists, and business teams to interpret data and implement solutions that enhance efficiency and reliability.

What is the difference between Statistical Engineer vs Data Scientist?

AspectStatistical EngineerData Scientist
Required CredentialsBachelor's or Master's in Statistics, Mathematics, or related field; often some programming skillsBachelor's or Master's in Data Science, Statistics, or related; strong programming and analytical skills
Work EnvironmentFocus on developing and optimizing statistical models, often in engineering or manufacturing settingsAnalyze large datasets, build predictive models, and communicate insights across various industries
Employer & Industry UsageUsed in manufacturing, engineering, and technology sectors for process improvementCommon in tech, finance, healthcare, and marketing for data analysis and modeling

While both roles require strong statistical knowledge and programming skills, Statistical Engineers primarily focus on developing and implementing statistical models within engineering contexts. Data Scientists tend to work more broadly on analyzing data, building predictive models, and deriving insights across diverse industries.

Is AI replacing statisticians?

Statistical engineers and statisticians use AI and machine learning tools to analyze data and develop models, but AI is not replacing these roles. Instead, AI enhances their capabilities, requiring professionals to have skills in programming, data analysis, and understanding AI algorithms to interpret and implement AI-driven solutions effectively.

What does a Statistical Engineer do?

A Statistical Engineer designs and applies statistical models and data analysis techniques to solve complex problems, often working with large datasets and programming tools like R or Python. They develop algorithms, optimize processes, and ensure data quality to support decision-making in engineering or manufacturing environments.

How does a Statistical Engineer typically collaborate with cross-functional teams in a project-driven environment?

Statistical Engineers often work closely with professionals from diverse fields such as data science, software engineering, quality assurance, and business analytics. In a project-driven environment, they are responsible for designing experiments, analyzing large datasets, and interpreting results to inform decision-making. Collaboration usually involves participating in regular meetings, communicating complex statistical findings in an accessible way, and ensuring that analytical methods align with the team's objectives. This cross-functional teamwork not only enhances project outcomes but also helps Statistical Engineers develop broader professional skills and a deeper understanding of the organization's operations.

What engineers make $500,000?

Senior engineers in specialized fields such as petroleum, aerospace, or software engineering can reach or exceed $500,000 annually, especially with bonuses, stock options, or in high-cost-of-living areas. These roles often require advanced skills, extensive experience, and sometimes professional certifications or advanced degrees.
What are popular job titles related to Statistical Engineer jobs in California? For Statistical Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Statistical Engineer jobs in California look for? The top searched job categories for Statistical Engineer jobs in California are:
Statistical Engineer jobs near you
Infographic showing various Statistical Engineer job openings in California as of June 2026, with employment types broken down into 97% Full Time, and 3% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $92,798 per year, or $44.6 per hour.
Associate Principal Statistical Analyst

Associate Principal Statistical Analyst

Revolution Medicines

Redwood City, CA • Hybrid

Other

Posted 15 days ago

Job description

The Opportunity:

Position requires about 10-14 years of Statistical Programming experience with exploratory-stage oncology clinical trials, providing programming support and oversight of one or more clinical programs (early or late phase) within Statistical Programming function. In addition to direct programming and technical oversight of one or more studies, this position may require assistance providing technical support and guidance during regulatory submissions while ensuring conformance to CDISC standards and submission guidelines. Titles may vary based on candidate experience. Based on company needs, this position may be required to lead an early Phase or late phase study or program. Specific responsibilities include:

  • Provide technical oversight of statistical programming resources including contractors and CROs.

  • Provide mentorship to future leaders to help learn and execute on RevMed core values.

  • Ensure quality and timely delivery of analysis for statistical programming deliverables.

  • Provide solutions by analyzing issues and problems in complex situations.

  • Ensure accuracy of clinical trial results for internal and external audiences (e.g., regulatory authorities, academic community, and healthcare providers) via QC of documents with clinical data.

  • Ensure that the statistical programming process conforms to the SOPs and regulatory standards where applicable.

  • Timeline and vendor management for deliverables, including submission-related activities, complying with regulatory standards (e.g., FDA 21 CFR Part 11, GxP).

  • Programming support for deliverables, such as Dose Committee meetings, Investigator Brochures, publications/presentations, US, and ex-US regulatory submissions.

  • Proficiency in regulatory standards and compliance regulations including CDISC compliance (SDTM, ADaM, define.xml, Reviewer's Guides, etc.).

Required Skills, Experience and Education:

  • 10-14 years of Statistical Programming experience in biotechnology or pharmaceutical industry.

  • BS/BA degree or other suitable qualification with relevance to the field.

  • Direct statistical programming experience for early or late-phase clinical trials to support production/verification of analysis datasets, tables, listings, and figures.

  • Demonstrated ability to multi-task, prioritize options, anticipate challenges, and execute goals as a member of an interdisciplinary team is extremely important.

Preferred Skills:

  • Early or late-stage oncology clinical trials.

  • A demonstrable record of strong leadership and teamwork.

  • Thrives in a collaborative team setting and is driven by a desire to deploy innovative approaches and technologies in a high energy environment.

#LI-Hybrid  #LI-DN1

Apply