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Statistical Engineering Jobs in California (NOW HIRING)

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Statistical Engineering information

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$61.8K

$72.4K

$80.8K

How much do statistical engineering jobs pay per year?

As of Jun 21, 2026, the average yearly pay for statistical engineering in California is $72,440.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,300.00 and $77,300.00 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 quantitative analysis skills, a background in statistics or mathematics, and often a relevant degree such as in engineering or applied statistics. Proficiency with statistical software (e.g., R, SAS, Python), data management systems, and sometimes Six Sigma certification is typically required. Critical thinking, problem-solving, and clear communication are crucial soft skills for interpreting data and collaborating with multidisciplinary teams. These skills ensure accurate data-driven decisions, efficient process improvements, and effective solutions to complex engineering challenges.

What engineers make $300,000 a year?

Senior statistical engineers or data science leaders with extensive experience, advanced skills in statistical modeling, programming, and data analysis can earn $300,000 or more annually. These roles often require advanced degrees, certifications, and leadership responsibilities in industries like finance, technology, or pharmaceuticals.

What do statistical engineers do?

Statistical engineers develop and implement statistical models and methods to analyze complex data, often focusing on process improvement and quality control. They use tools like statistical software and programming languages such as R or Python and collaborate with data scientists and engineers to optimize systems and decision-making processes.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, petroleum engineering, and certain roles in financial engineering can earn $500,000 or more annually, often including bonuses and stock options. High compensation typically requires extensive experience, advanced skills, and working in high-demand industries or leadership positions.

What is the difference between Statistical Engineering vs Data Scientist?

AspectStatistical EngineeringData Scientist
Required credentialsStatistics, Data Analysis, EngineeringStatistics, Computer Science, Data Analysis
Work environmentManufacturing, R&D, Engineering teamsBusiness, Tech, Research sectors
Employer usageOptimizing processes, designing experimentsBuilding models, insights, predictive analytics

Statistical Engineering focuses on applying statistical methods to improve engineering processes and product development, often within manufacturing or R&D settings. Data Scientists analyze large datasets to extract insights, build predictive models, and support business decisions. While both roles require strong statistical skills, Statistical Engineering emphasizes process optimization and experimental design, whereas Data Scientists focus on data-driven insights across diverse industries.

How much does a Statistical Engineer make?

The average salary for a Statistical Engineer typically ranges from $70,000 to $120,000 annually, depending on experience, education, and location. Professionals in this role often use statistical software and data analysis tools, and advanced skills can lead to higher compensation.

How does a Statistical Engineer typically collaborate with cross-functional teams to implement data-driven solutions?

Statistical Engineers frequently work alongside data scientists, software engineers, and business analysts to design and implement robust data-driven solutions. They are responsible for translating complex statistical models into actionable insights and ensuring that these models are integrated effectively within existing systems. Collaboration often involves regular meetings to align on project goals, sharing progress updates, and troubleshooting technical challenges together. This interdisciplinary teamwork is essential for ensuring that statistical methodologies are not only theoretically sound but also practically applicable to real-world business problems.

What is statistical engineering?

Statistical engineering is an interdisciplinary field that focuses on the integration and application of statistical methods and principles to solve complex, large-scale problems in science, business, and engineering. It involves designing data collection processes, analyzing and interpreting data, and implementing statistical solutions within larger systems. Statistical engineers often work on projects that require collaboration with other engineering disciplines, using statistics as a foundational tool to drive decision-making and innovation.
What are popular job titles related to Statistical Engineering jobs in California? For Statistical Engineering jobs in California, the most frequently searched job titles are:
What job categories do people searching Statistical Engineering jobs in California look for? The top searched job categories for Statistical Engineering jobs in California are:
What cities in California are hiring for Statistical Engineering jobs? Cities in California with the most Statistical Engineering job openings:
Statistical Engineering jobs near you
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

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