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Phd In Statistics Jobs (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 ...

AstraZeneca

Statistical Science Director

Wilmington, DE · On-site

PhD in Statistics Join the team unlocking the power of what science can do. We are working towards treating, preventing, modifying and even curing some of the world's most complex diseases. Here we ...

AstraZeneca

Statistical Science Director

Wilmington, DE · On-site

PhD in Statistics Join the team unlocking the power of what science can do. We are working towards treating, preventing, modifying and even curing some of the world's most complex diseases. Here we ...

AstraZeneca

Statistical Science Director

Wilmington, DE · On-site

PhD in Statistics Join the team unlocking the power of what science can do. We are working towards treating, preventing, modifying and even curing some of the world's most complex diseases. Here we ...

AstraZeneca

Statistical Science Director

Wilmington, DE · On-site

PhD in Statistics Join the team unlocking the power of what science can do. We are working towards treating, preventing, modifying and even curing some of the world's most complex diseases. Here we ...

Indiana University

Postdoctoral Fellow

Bloomington, IN · On-site

$45K - $61K/yr

PhD in Psychology, Educational Psychology, Cognitive Science, or related field * Strong communication and interpersonal skills * Expertise in statistics and data management (using R) Preferred:

Point72

Equity Quantitative Researcher

New York, NY · On-site

MS or PhD in physics, engineering, statistics, applied math, quantitative finance or other quantitative fields with a strong foundation in statistics * 1+ years of work experience in systematic alpha ...

Jazz Pharmaceutical

Sr Principal Statistician

Palo Alto, CA · On-site

$102K - $125K/yr

PhD in statistics, mathematics, or a related discipline with a statistical focus and > 2 years of experience in the pharmaceutical or biotechnology industry. * Knowledge of drug development ...

Point72

Equity Quantitative Researcher

New York, NY

MS or PhD in physics, engineering, statistics, applied math, quantitative finance or other quantitative fields with a strong foundation in statistics * 1+ years of work experience in systematic alpha ...

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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 can you do with a PhD in statistics?

A PhD in statistics prepares individuals for advanced roles in data analysis, research, and consulting across industries such as healthcare, finance, technology, and government. Graduates often work as data scientists, statisticians, quantitative analysts, or research scientists, utilizing skills in statistical modeling, programming, and data management. The degree also enables careers in academia and research institutions, often requiring proficiency in tools like R, Python, or SAS.

How much can you make with a PhD in statistics?

A PhD in statistics typically leads to high-paying roles such as data scientist, quantitative analyst, or research scientist, with salaries often 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 a PhD in statistics worth it?

A PhD in statistics can lead to advanced roles in research, data science, and academia, often requiring strong analytical and programming skills. While it offers high-level expertise and potential for higher salaries, it also involves significant time and financial investment, and job prospects depend on industry demand and individual specialization.

Is AI replacing statisticians?

AI is transforming the role of statisticians by automating routine data analysis tasks and enabling more complex modeling, but it does not replace the need for expert statistical judgment, interpretation, and domain knowledge. Statisticians are increasingly using AI tools and programming languages like R or Python to enhance their work, making their skills still essential in designing studies and ensuring data quality.
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Phd In Statistics jobs near you
Infographic showing various Phd In Statistics job openings in the United States as of June 2026, with employment types broken down into 79% Full Time, and 21% Part Time. Highlights an 90% Physical, 4% Hybrid, and 6% Remote job distribution.
Data Scientist

Data Scientist

Apex Informatics

Pleasanton, CA • On-site

Contractor

Posted 29 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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