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Phd Data Scientist Jobs (NOW HIRING)

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 ...

Data Scientist

San Ramon, CA · On-site

$93 - $98/hr

PhD in engineering or a related field. * Experience with AWS, Azure, cloud computing technologies. * Experience designing efficient data science workflows and database architecture. * Experience with ...

Our Team Enthusiasm, skepticism, and respect for data are in our DNA - two of our co-founders were PhD data scientists at Robinhood. Since our founding, we have grown the team to include perspectives ...

Data Scientist Location: Sunnyvale Duration: 6 Months + Minimum Qualifications - PhD in Computer Science, Statistics or related field; OR a Master's degree or equivalent in Computer Science ...

Master's degree or PhD in Data Science, Statistics, Computer Science, Machine Learning, or related field, or equivalent experience. * 9+ years of experience in data science, machine learning ...

Data Scientist Location: Sunnyvale Duration: 6 Months + Minimum Qualifications - PhD in Computer Science, Statistics or related field; OR a Master's degree or equivalent in Computer Science ...

Conversica is seeking talented and passionate data scientists to help us evolve our artificial ... Masters/PhD preferred. Ideally we would like to see someone that has been published in Natural ...

Data Scientist Location: Sunnyvale, CA Sponsorship: Yes Relocation: Yes Industry: eCommerce Are you ... PhD in Computer Science, Statistics or related field; OR a Master's degree or equivalent in ...

Data Scientist

San Francisco, CA · On-site +1

$160K - $200K/yr

The role will report directly to the CTO. Next to the CTO, you will be first Data Scientist on the ... either PhD or Advanced MS degree. * Comfortable with Python, Flask/Django, Pandas and Numpy

As a Senior Data Scientist, you will play a pivotal role in our data science efforts, with ... or PhD in a quantitative discipline, especially Statistics, Math, or similar • Strong ...

PhD preferred in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field. * 7+ years of experience along with a PhD in a related field ...

We were built from scratch with PhD data scientists and award-winning creatives working on the same briefs, from day one. That structure earned us an Ad Age #3 A-List ranking, back-to-back Data ...

The Data Scientist at the Analyst / Team Lead level is responsible for solving complex business ... Masters, MBA, JD, MD, or PhD). Preferred Qualifications: * 3 or more years of work experience with ...

We were built from scratch with PhD data scientists and award-winning creatives working on the same briefs, from day one. That structure earned us an Ad Age #3 A-List ranking, back-to-back Data ...

Data Scientist

San Francisco, CA · Remote

$160K - $200K/yr

The role will report directly to the CTO. Next to the CTO, you will be first Data Scientist on the ... either PhD or Advanced MS degree. * Comfortable with Python, Flask/Django, Pandas and Numpy

PhD in a quantitative field * A demonstrated track record of independently driving data science projects to deliver business value * Experience solving problems related to Autonomous Driving or Ride ...

PhD preferred in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field. * 7+ years of experience along with a PhD in a related field ...

Showing results 41-60

Phd Data Scientist information

See salary details

$46K

$165K

$243.5K

How much do phd data scientist jobs pay per year?

As of Sep 2, 2026, the average yearly pay for phd data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a PhD data scientist?

PhD Data Scientists are professionals who have earned a doctoral degree (PhD) in a relevant field, such as computer science, statistics, mathematics, or engineering, and work in roles focused on analyzing and interpreting complex data. They leverage advanced research skills, deep theoretical knowledge, and expertise in data modeling to solve challenging problems, build predictive models, and derive actionable insights for organizations. PhD Data Scientists often contribute to cutting-edge projects, publish research, and help bridge the gap between academic research and practical, real-world applications.

What are the key skills and qualifications needed to thrive as a PhD data scientist?

To thrive as a PhD Data Scientist, you need advanced expertise in statistics, machine learning, and data analysis, typically backed by a PhD in a quantitative field. Proficiency with programming languages like Python or R, experience with big data tools (e.g., Hadoop, Spark), and familiarity with cloud platforms and version control systems are commonly required. Strong problem-solving skills, communication abilities, and the capacity to explain complex concepts to non-technical stakeholders are crucial soft skills. These skills and qualities are essential for extracting actionable insights from complex datasets and driving data-informed decision-making in organizations.

What are some common challenges PhD data scientists face when transitioning from academia to industry roles?

PhD Data Scientists often encounter challenges when moving from academia to industry, such as adapting to faster project timelines, prioritizing business impact over exploratory research, and communicating complex findings to non-technical stakeholders. In industry, there is a greater emphasis on collaborative teamwork and delivering actionable insights that align with organizational goals. Building skills in agile development, stakeholder engagement, and product-focused thinking can help smooth the transition and ensure success in a corporate environment.

What is the difference between Phd Data Scientist vs Data Analyst?

AspectPhd Data ScientistData Analyst
Required CredentialsPhD or Master's in Data Science, Statistics, or related fieldBachelor's or Master's in related field, often with certifications
Work EnvironmentResearch-focused, complex modeling, advanced analyticsBusiness reporting, data visualization, basic analysis
Employer & Industry UsageTech, academia, research institutions, large corporationsBusiness, marketing, finance, healthcare

Phd Data Scientists typically have advanced degrees and focus on complex modeling and research, while Data Analysts handle more straightforward data reporting and visualization tasks. Both roles are essential in data-driven organizations but differ in scope and expertise.

More about Phd Data Scientist jobs

What cities are hiring for Phd Data Scientist jobs?

Cities with the most Phd Data Scientist job openings:

What states have the most Phd Data Scientist jobs?

States with the most job openings for Phd Data Scientist jobs include:

Infographic showing various Phd Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Scientist

Apex Informatics

Pleasanton, CA • On-site

Contractor

Re-posted 14 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.