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Statistical Data Jobs in California (NOW HIRING)

Works collaboratively with Clinical Development staff to meet project deliverables and timelines for statistical data analysis and reporting. * Generates or oversees the production of programming ...

The Statistical Programmer interfaces with Statistics, Data Sciences and Clinical Operations. Job ... Responsibilities: * Develop SAS programs for the creation of ADaM data sets following CDISC ...

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Statistical Data information

What is a statistical data analyst?

Statistical data analysts are professionals who collect, process, and interpret quantitative data to help organizations make informed decisions. They use statistical techniques and software tools to analyze datasets, identify trends, and solve problems. Their work is crucial in fields such as business, healthcare, government, and research, where data-driven insights are essential. Statistical data analysts often present their findings in reports or visualizations to guide strategic planning.

What are the key skills and qualifications needed to thrive as a statistical data analyst, and why are they important?

To thrive as a Statistical Data Analyst, you need strong quantitative skills, expertise in statistics, and a relevant degree such as mathematics, statistics, or data science. Proficiency with tools like R, Python, SQL, and statistical software (e.g., SPSS, SAS) as well as data visualization platforms is typically required. Critical thinking, attention to detail, and effective communication skills help analysts interpret data accurately and share insights with stakeholders. These competencies ensure reliable data analysis, support evidence-based decisions, and drive organizational success.

What are some common challenges faced by professionals working in statistical data roles, and how can they be addressed?

Professionals in statistical data roles often encounter challenges such as managing large, complex datasets, ensuring data quality, and effectively communicating statistical findings to non-technical stakeholders. Dealing with incomplete or inconsistent data is common, and requires strong analytical and problem-solving skills to clean and validate information. Collaborating closely with cross-functional teams, staying updated on the latest statistical software, and developing clear data visualization skills can help address these challenges and enhance the impact of your work.

What is the difference between Statistical Data vs Data Analyst?

AspectStatistical DataData Analyst
Required CredentialsNone specific; often involves understanding data collectionBachelor's degree in statistics, data science, or related field
Work EnvironmentData collection, storage, and management environmentsAnalyzing data, creating reports, and visualizations
Industry UsageUsed across industries for data collection and storageApplied in business, finance, healthcare, and more for insights
Search & Comparison IntentUnderstanding raw data types and sourcesComparing roles focused on data analysis and interpretation

Statistical Data refers to raw or processed data used for analysis, while Data Analyst is a professional role that interprets and visualizes this data to support decision-making. Both are integral to data-driven industries but serve different functions within the data lifecycle.

What job categories do people searching Statistical Data jobs in California look for?

The top searched job categories for Statistical Data jobs in California are:

What cities in California are hiring for Statistical Data jobs?

Cities in California with the most Statistical Data job openings:

Infographic showing various Statistical Data job openings in California as of June 2026, with employment types broken down into 6% As Needed, 51% Full Time, 8% Part Time, 4% Temporary, 28% Contract, and 3% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Scientist (Statistician)

Brain Resource

San Francisco, CA • On-site

Full-time

Re-posted 20 days ago


Job description

Company Description
Brain Resource's mission is to make sense of the brain's complexities and provide a coherent model for measuring brain health. Healthcare requires evidence-based data and reliable benchmarks in order to improve the way decisions in brain health. Brain Resource established the first and largest international human brain database.
Our research sector conducted the International Studies to Predict Optimized Treatment (iSPOT) Response - in Depression and ADHD and is focused on a single goal: to improve the treatment outcomes for millions with Depression and ADHD by identifying objective tests to predict treatment response.
Job Description
We are seeking a data scientist (statistician) to aid with the analysis of the data collected in our iSPOT studies (see http://www.brainresource.com/research/ispot). The Depression component of this study aims to identify biomarkers that can objectively predict which antidepressants are most likely to help which people with depression, and to develop a range of tests that have real-world application. The ADHD component aims to identify biomarkers that can predict which children/adolescents have ADHD and will respond to stimulant medications. Taking an integrative neuroscience approach, these studies span clinical, cognitive, psychophysiological, imaging and genomic data, and has 20 peer-reviewed publications to date. You will be involved in the design and running of analyses, and writing up these methods and results.
Additionally we require a range of analyses that further explore data in the Brain Resource International Database, which now has several hundred thousand datasets.
This is a high profile position in a world leading study, with a global multidisciplinary team from a range of academic institutions and backgrounds.
This position is based in San Francisco, CA.
Qualifications
Required Attributes
• Graduate degree or equivalent, with experience in research and statistical analysis
• Experience using the R statistical package (or Python/Scala) at an advanced level, including scripting, automated analyses and data visualization.
• Strong experience with statistical data analysis for the social sciences or equivalent human clinical datasets
• Sound knowledge of and experience with predictive statistics (with preferred experience in cross validation or similar techniques)
• Experience with large datasets (with preference for multidisciplinary data experience)
• Highly skilled in distilling complicated results and openly communicating challenges
• Excellent communication and interpersonal skills, with demonstrated ability to liaise effectively with a range of people (e.g., senior management and other researchers from a range of disciplines)
• Highly developed organizational skills, including prioritization and time management
• Strong ability to work both independently and as part of a team
• Demonstrated problem solving skills and a strong focus on solutions
• Ability to contribute to publications
• Ability to present outcomes to a range of interested audiences
Preferred Attributes
• Preferred statistical experience includes a good understanding and use of logistic regression, predictive models, multiple imputation, spline regression, linear mixed models for dose/regime type trial designs, simulations, cross validation, correction for multiple testing, principle components analysis.
• Experience with bash scripting and pipeline development. programming for parallel computing
• Experience in pharmaceutical or large clinical trials, particularly in the planning, design or data analysis.
• Experience with submissions to the FDA
• Experience in the field of neuroscience, psychology or psychometrics.
• Knowledge of genetics microarray/SNP data or EEG data analysis
Additional Information
This is a full-time position. Salary will be dependent on the experience and skills of the applicant. The position is located at our San Francisco office in the Financial District.
To apply, please include a CV and cover letter addressing the necessary skills and experience outlined above. Applications and further enquiries should be directed to: Donna Palmer.