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Statistical Engineering Jobs in Berkeley, CA (NOW HIRING)

Gilead

Sr Manager, Statistical Programming

Foster City, CA · On-site

$169K - $219K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Statistical programmers work collaboratively with internal colleagues and external vendors to ensure the efficient, high-quality production of analysis datasets and statistical outputs for study ...

Gilead

Assoc Director, Statistical Programming

Foster City, CA

$195K - $253K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Statistical programmers work collaboratively with internal colleagues and external vendors to ensure the efficient, high-quality production of analysis datasets and statistical outputs for study ...

Gilead

Sr Manager, Statistical Programming

Foster City, CA

$169K - $219K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Statistical programmers work collaboratively with internal colleagues and external vendors to ensure the efficient, high-quality production of analysis datasets and statistical outputs for study ...

Gilead

Assoc Director, Statistical Programming

Foster City, CA

$195K - $253K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Statistical programmers work collaboratively with internal colleagues and external vendors to ensure the efficient, high-quality production of analysis datasets and statistical outputs for study ...

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Showing results 1-20

All JobsStatistical Engineering JobsStatistical Engineering Jobs in Berkeley, CA

Statistical Engineering information

See Berkeley, CA salary details

$30.7K

$116.4K

$202.7K

How much do statistical engineering jobs pay per year?

As of Aug 17, 2026, the average yearly pay for statistical engineering in Berkeley, CA is $116,408.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,839.00 and $149,678.00 per year, depending on experience, location, and employer.

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.

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 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 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.

What job categories do people searching Statistical Engineering jobs in Berkeley, CA look for?

The top searched job categories for Statistical Engineering jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Statistical Engineering jobs?

Cities near Berkeley, CA with the most Statistical Engineering job openings:

Statistical Engineering jobs near you

Associate Director, Statistical Programming

Revolution Medicines

Redwood City, CA • Hybrid

Full-time

Re-posted 5 days ago

Job description

The Opportunity:

Position requires 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 hands-on Programming, this position requires providing oversight and programming support and guidance for internal deliverables and regulatory submissions while ensuring conformance to CDISC standards and submission guidelines. Based on company needs, this position will be required to lead one or more early Phase or late phase studies/programs. Specific responsibilities include:

  • Effective collaborating with cross functional teams to provide programming timelines for various deliverables.

  • Provide SAS Programming technical support and guidance to programming team.

  • Oversight/participation in any internal/mock or regulatory authority audits.

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

  • Oversee the programming support for relevant deliverables, such as Investigator Brochures, publications, US and ex-US regulatory submissions, including CDISC compliant datasets (SDTM, ADaM) and data documentation, Reviewer's Guide, TLFs, Statistical Analysis Plans (study specific, ISS, ISE, Exposure-Response), blank and annotated CRFs, and actual patient CRFs.

  • Hands-on programming and management of in-house deliverables including but not limited to Dose Committee meetings, Board of Director meetings, Exploratory Analysis, etc.

  • Oversight and Verification Review of documents, spreadsheets, slides for in-house presentations and external publications.

Titles may vary based on candidate experience.

Required Skills, Experience and Education:

  • 14+ years of Statistical Programming experience with early or late phase oncology trial studies.

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

  • Experience leading one or more statistical programming contractors, and programming vendors.

  • Proficiency in providing hands-on SAS Programming support for production or validation 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:

  • 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.

  • Experience working in a small to mid sized biotech/pharma environment.

  • Experience collaborating on development of processes, SOPs and guidance documents for the Statistical Programming function. 

    #LI-Hybrid  #LI-DN1

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