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Phd In Statistics Jobs in California (NOW HIRING)

Apex Informatics

Data Scientist

Pleasanton, CA · On-site

Experience manipulating data sets and building statistical models, has a Master's or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following ...

Brilent

Data Scientist Intern

San Mateo, CA · On-site

Pursuing BS, MS or PhD in Statistics, Applied Mathematics, Computer Science or another quantitative discipline. Advanced degree preferred * Proficient in SQL and able to write complex SQL queries

Genentech

Senior Statistician

South San Francisco, CA

$136K - $254K/yr

You hold an MSc or PhD in Statistics, Biostatistics, or a closely related quantitative field * You have a minimum of 3 years of relevant experience in clinical trial statistics within a ...

Exelixis

Executive Director, Biostatistics

Alameda, CA · On-site

PhD in Statistics/Biostatistics or related discipline and a minimum of 15 years of related experience; or, * Equivalent combination of education and relevant experience in oncology. * May require ...

Exelixis

Sr Director, Biostatistics

Alameda, CA

PhD in Statistics/Biostatistics or related discipline and a minimum of 12 years of related experience; or, * Equivalent combination of education and relevant experience in oncology. Experience/The ...

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All JobsPhd In Statistics JobsPhd In Statistics Jobs in California

Phd In Statistics information

What is the difference between Phd In Statistics vs Data Scientist?

AspectPhd In StatisticsData Scientist
Required CredentialsTypically a PhD in Statistics or related fieldOften a bachelor's or master's degree in a quantitative field; some roles prefer a PhD
Work EnvironmentAcademic, research institutions, or specialized analytics teamsCorporate, tech companies, or consulting firms
Industry UsageResearch, academia, government, and industry R&DBusiness analytics, product development, and data-driven decision making
Common Search & ComparisonYesYes

While a Phd In Statistics focuses on advanced research, theoretical development, and academic roles, Data Scientists apply statistical and machine learning techniques to solve practical business problems. Both roles require strong analytical skills, but Data Scientists often work in more applied, industry-focused environments, whereas PhD holders may pursue research or academic careers.

What is the highest paying job with a statistics degree?

The highest paying jobs with a statistics degree often include roles such as data scientist, quantitative analyst, or actuarial scientist, with salaries exceeding $100,000 annually. Senior positions in finance, technology, or consulting firms tend to offer the highest compensation, especially for those with advanced skills in machine learning, programming, and statistical modeling.

How much can you make with a PhD in statistics?

A PhD in statistics can lead to high-paying roles such as data scientist, quantitative analyst, or research scientist, with salaries typically ranging from $90,000 to over $150,000 annually depending on experience, industry, and location. Advanced skills in programming, statistical software, and data analysis increase earning potential in this field.

Is getting a PhD in statistics worth it?

A PhD in statistics prepares individuals for advanced research, academia, and data science roles that require deep analytical skills and expertise in statistical methods. It can lead to higher-level positions and increased earning potential but involves significant time and financial investment. The decision depends on career goals and the demand for specialized statistical knowledge in the desired industry.

What can I do with PhD in statistics?

A PhD in statistics qualifies individuals for advanced roles such as data scientist, quantitative analyst, biostatistician, or research scientist. These positions often involve data analysis, modeling, and interpretation using statistical software like R or SAS, and may require collaboration across industries such as healthcare, finance, or technology.
What are popular job titles related to Phd In Statistics jobs in California? For Phd In Statistics jobs in California, the most frequently searched job titles are:
What job categories do people searching Phd In Statistics jobs in California look for? The top searched job categories for Phd In Statistics jobs in California are:
What cities in California are hiring for Phd In Statistics jobs? Cities in California with the most Phd In Statistics job openings:
Phd In Statistics jobs near you
Infographic showing various Phd In Statistics job openings in California as of July 2026, with employment types broken down into 100% Full Time. Highlights an 71% In-person, and 29% Remote job distribution.
Data Scientist

Data Scientist

Apex Informatics

Pleasanton, CA • On-site

Contractor

Posted 5 days ago

Job description

Job Details: Data Scientist
Location: Pleasanton, CA
Top Skill:
Qualifications for Data Scientist Strong problem solving skills with an emphasis on product development.
Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests anritaprikhodkod proper usage, etc.) and experience with applications.
Experience manipulating data sets and building statistical models, has a Master's or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software tools: Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.
Knowledge and experience in statistical and data mining techniques: GLM Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc
Experience querying databases and using statistical computer languages: R, Python, SLQ, etc. Experience using web services: Redshift, S3, Spark, , etc.
Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc
Experience analyzing data from 3rd party providers: Client Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Client Insights, etc. Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc. Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
Top Daily Responsibilities:
1. Support Data-Science and other analytics as needed.
2. Develop SQL queries and data sets 3. Develop business and client facing reports
Skills a Top Candidate Should Have:
  • Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
  • Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
  • Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
  • Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
  • Experience analyzing data from 3rd party providers: Client Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Client Insights, etc.
  • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
  • Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.

Desired Skills:
  • Strong problem solving skills with an emphasis on product development.
  • Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
  • Experience working with and creating data architectures.
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • Excellent written and verbal communication skills for coordinating across teams.
  • A drive to learn and master new technologies and techniques.
  • We're looking for someone with experience manipulating data sets and building statistical models, has a Master's or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with software.

Skills:
1. Excellent Communication Skills.
2. Ability to work with business to gather report requirements.
3. Team player. Custom Job Description: If you have a custom job description that you would like to use. Please paste it here: Knowledge and experience with large data sets, event streams and distributed computing (Hive,Impala,Hadoop etc.) Ability to gather requirements and develop reports in tool selected by business and KPIT.

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