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Associate Director Statistical Programming Jobs in Sunnyvale, CA

RXinsider LTD.

Associate Director Engineering

Milpitas, CA · On-site

$183.80 - $294.10/hr

Position Summary The Associate Director of Engineering is the senior engineering leader at the site level, responsible for engineering execution, technical governance, and performance. This role ...

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Associate Director Statistical Programming information

See Sunnyvale, CA salary details

$180.2K

$328.8K

$403.7K

How much do associate director statistical programming jobs pay per year?

As of Aug 7, 2026, the average yearly pay for associate director statistical programming in Sunnyvale, CA is $328,795.00, according to ZipRecruiter salary data. Most workers in this role earn between $305,700.00 and $378,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an associate director statistical programming?

To thrive as an Associate Director Statistical Programming, you need expertise in statistical programming, clinical trial data standards, and a degree in statistics, mathematics, or a related field, often with several years of experience in the pharmaceutical or biotechnology industry. Proficiency in programming languages such as SAS and R, knowledge of CDISC standards (SDTM, ADaM), and familiarity with regulatory submission requirements are typically required. Strong leadership, project management, and communication skills are vital for guiding teams and collaborating with cross-functional partners. These skills and qualities ensure the delivery of high-quality, compliant statistical outputs that support clinical development and regulatory approval.

What does an associate director statistical programming do?

An Associate Director of Statistical Programming leads teams responsible for the design, development, and validation of statistical programs used in the analysis of clinical trial data. They oversee the creation of datasets, tables, listings, and figures that support regulatory submissions and scientific publications. In addition to technical expertise, this role involves managing timelines, ensuring compliance with regulatory standards, and collaborating with cross-functional teams such as biostatistics, data management, and clinical operations.

How does an associate director statistical programming typically collaborate with cross-functional teams in a pharmaceutical or biotech setting?

As an Associate Director of Statistical Programming, you will work closely with biostatisticians, clinical data managers, and regulatory affairs professionals to ensure that statistical analyses and data outputs meet project and regulatory requirements. You’ll often lead programming teams, coordinate timelines, and help translate statistical analysis plans into executable code. Regular meetings and clear communication are key, as you’ll be expected to provide technical guidance and ensure data integrity across multiple studies or programs. This role often requires balancing hands-on programming with strategic leadership and mentorship responsibilities.

What is the difference between Associate Director Statistical Programming vs Statistical Programmer?

AspectAssociate Director Statistical ProgrammingStatistical Programmer
Required CredentialsBachelor's or Master's in Biostatistics, Statistics, or related field; experience in clinical trial programmingBachelor's or Master's in similar fields; entry to mid-level experience
Work EnvironmentLeads teams, manages projects, collaborates with cross-functional teamsPerforms programming tasks, supports project teams, executes statistical analyses
Employer & Industry UsagePharmaceutical and biotech companies, clinical research organizationsPharmaceutical companies, CROs, biotech firms

The Associate Director Statistical Programming typically oversees programming teams and manages project deliverables, requiring leadership skills and extensive experience. In contrast, the Statistical Programmer focuses on executing programming tasks under supervision. Both roles are essential in clinical research, but the Associate Director holds more managerial responsibilities and strategic oversight.

What are popular job titles related to Associate Director Statistical Programming jobs in Sunnyvale, CA? For Associate Director Statistical Programming jobs in Sunnyvale, CA, the most frequently searched job titles are:
What job categories do people searching Associate Director Statistical Programming jobs in Sunnyvale, CA look for? The top searched job categories for Associate Director Statistical Programming jobs in Sunnyvale, CA are:
What cities near Sunnyvale, CA are hiring for Associate Director Statistical Programming jobs? Cities near Sunnyvale, CA with the most Associate Director Statistical Programming job openings:
Associate Director Statistical Programming jobs near you
Infographic showing various Associate Director Statistical Programming job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $328,795 per year, or $158.1 per hour.

Associate Director, Medical Analytics and Exploratory Data Science

Revolution Medicines

Redwood City, CA • Hybrid

$72K - $72K/yr

Full-time

Re-posted 25 days ago

Job description

The Opportunity:

We are seeking a highly capable Associate Director of Biostatistics to join our Medical Analytics and Exploratory Data Science Biostatistics group within our Biostatistics organization. This role will play a critical part in the design, analysis, and interpretation of exploratory data analyses, scientific publications, real-world evidence (RWE), post-marketing research, and health economics and outcomes research (HEOR) studies. The successful candidate will serve as a key statistical contributor and emerging leader, partnering closely with cross-functional teams to deliver high-quality, data-driven insights that support scientific understanding and evidence generation.

  • Lead statistical design, analysis, and interpretation for exploratory data analyses using existing clinical trial data, real world data studies, post-marketing research, and HEOR projects.

  • Partner closely with other subfunctions within quantitative sciences and with cross-functional teams, including clinical development, medical affairs, safety, statistical programming, regulatory affairs and commercial, to execute evidence generation plans.

  • Apply appropriate statistical methodologies, including survival analysis, machine learning, and casual inference approaches, to address complex scientific and medical questions in oncology.

  • Contribute to the development of analysis plans, technical specifications, and interpretation of results under general direction from senior statistical leadership.

  • Support cross-functional evidence generation planning by providing statistical input into study design, feasibility, and analysis strategies.

  • Review and oversee statistical deliverables produced by internal programmers or external vendors/contractors to ensure scientific quality and consistency with standards.

  • Contribute to and implement policies, standards, and procedures to ensure consistency and quality in statistical practices.

  • Assist with the preparation of scientific communications, including abstracts, manuscripts, posters, and internal presentations.

Required Skills, Experience and Education:

  • Ph.D. or M.S. in Statistics/Biostatistics, a minimum of 5 years (for Ph.D.) and 8 years (for M.S.) of experience in biotech/pharma industry as a statistician.

  • Solid knowledge of statistical methodologies for oncology, including survival analysis and causal inference.

  • Hands-on experience in exploratory analysis of oncology trials.

  • Ability to work independently and within a team.

  • Ability to independently execute statistical analyses for moderately complex projects with guidance from senior statisticians.

  • Familiar with regulatory requirements related to biostatistical activities and clinical trials.

  • Strong verbal and written communication skills are required.

  • Strong interpersonal and project management skills are essential.

  • Proficiency in SAS and/or R.

Preferred Skills:

  • Knowledge of RWD and health economics and outcomes research (HEOR) in oncology is a plus.

  • Familiarity with machine learning or advanced modeling approaches applied to biomedical or observational data. 

    #LI-Hybrid  #LI-SH1

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