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Statistical Engineering Jobs in Berkeley, CA (NOW HIRING)

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$30.7K

$116.4K

$202.7K

How much do statistical engineering jobs pay per year?

As of Jun 11, 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 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 Berkeley, CA? For Statistical Engineering jobs in Berkeley, CA, the most frequently searched job titles are:
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

Senior Manager, Statistical Programming

Kardigan

South San Francisco, CA

Other

Posted 15 days ago

Job description

Position Title: Senior Manager, Statistical Programming

Department: Clinical Data Sciences & Analytics 

Reports To: Head of Statistical Programming

Location: South San Francisco, CA or Princeton, NJ - On-site 4 days per week (Mon to Thurs) 

Job Overview:

The Senior Manager of Statistical Programming will be responsible for leading Statistical Programming activities. It involves hands-on implementation of statistical analyses using SAS/R, as well as performing quality reviews of deliverables, both for in-house analyses and outsourced programming tasks.

This position serves as a critical bridge between Biostatistics and Clinical Data Management (CDM), ensuring the development of CRFs and the delivery of high-quality clinical data. Additionally, this position will play an important role in helping establish SOPs and programming standards and also build our SCE platform.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Key Project Responsibilities:

  • Provides programming leadership and oversee study to compound-level programming deliverable in collaboration with the Stats lead and cross-functional teams.
  • Serve as the lead programmer to reviews SAP, Data Presentation Plan, Table Shell to align with project objectives and ensures clarity and completeness of programming assumptions and requirements.
  • Lead programming team to produce and/or validate SDTM, ADaM and TLF, for CSR and regulatory requests, publication needs, and ad-hoc analyses.
  • Manage CROs and contractors, ensuring compliance, quality of deliverables, timelines, and budget adherence.
  • Collaborate with biostatisticians and clinical development colleagues to develop/review TLF shells, SDTM, and ADaM specifications.
  • Work closely with Data Management and Biostatistics teams to ensure the accuracy of final databases, analyses, and reports.
  • Develop global tools, such as macros or graphical user interface applications, to enhance the efficiency and capacity of the Statistical Programming team.
  • Develops robust program to create define.xml, Leads the NDA eSubmission package preparation.
  • Assist Biometric in building the statistical computing environment (SCE) platform, including designing folder structure and managing access control.

Initiative Responsibilities:

  • Under guidance from Head of Statistical Programming and Compound PL, implement innovative strategies and technologies to enhance programming processes.
  • Working with manager, establish Statistical Programming standard and deploy programming strategies, specifications and programmed analysis.
  • Proactively plan, implement, and identify issues/risks and provide remediation strategies to improve programming capability.

Qualifications and Preferred Skills

Education:

  • Master's degree in Statistics/Biostatistics, Mathematics, Computer Science, or a related field.

Experience and Skill Set:

  • Minimum of 6 years statistical programming experience in the pharmaceutical, biotech or CRO clinical trial environment.
  • Advanced SAS programming skills. Extensive Hands-on experience with SDTM, ADaM, TLF programming
  • Proficient knowledge in the implementation of CDISC standards (SDTM, ADaM) and regulatory submission requirements.
  • Good knowledge of drug development process, study design, statistical methodology, regulatory guidance, statistical concepts, and medical terminology.
  • Broad expertise in statistical programming and in developing computing strategies.
  • In-depth understanding of CDISC standards including SDTM and ADaM models and extensive experience of their implementation in clinical trials.
  • Demonstrated proficiency in using SAS/R to produce analysis datasets and TFLs.
  • Knowledge of data validation, define.xml generation using Pinnacle 21.
  • Results orientated with proven problem-solving skills and a strong interest in ongoing learning.
  • Excellent communication and collaboration skills, with the ability to work closely with cross-functional teams
  • Experience managing outsourced programming activities and overseeing deliverables from CROs and contractors.
  • Adaptable and thrives in a fast-paced, startup environment while managing multiple priorities effectively.
  • Experience with regulatory audits and inspections and IR (e.g., FDA, PMDA, NMPA, EMA) is a strong advantage.

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