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Causal Inference Phd Internship Jobs (NOW HIRING)

Docugami

Data Science PhD Intern

Kirkland, WA · On-site

We're now looking for AI, NLP, Machine Learning, Data Science, and Math PhD Interns to work ... causal inference, and other related disciplines * Programming skills and familiarity of modern ML ...

Docugami

Data Science PhD Intern

Kirkland, WA · On-site

We're now looking for AI, NLP, Machine Learning, Data Science, and Math PhD Interns to work ... causal inference, and other related disciplines * Programming skills and familiarity of modern ML ...

Roku

Senior Research Data Scientist

Boston, MA · On-site

$330K - $375K/yr

PhD in Economics, Econometrics, Statistics, or a closely related quantitative field with a strong emphasis on causal inference * 10+ years of experience applying causal inference and machine learning ...

Apple

Applied Scientist

Austin, TX · On-site

You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... PhD in related field Hands-on experience leveraging Generative AI to improve productivity and ...

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How much do causal inference phd internship jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for causal inference phd internship in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What types of projects do Causal Inference PhD interns typically work on during their internship?

Causal Inference PhD interns often engage in projects that involve designing and analyzing experiments or observational studies to draw valid conclusions about cause-and-effect relationships. These projects might include developing statistical models, collaborating with data scientists and product teams, and presenting findings to inform business or policy decisions. Interns usually have the opportunity to work with large-scale, real-world data, and are encouraged to publish or present their work at conferences, supporting both professional growth and academic development.

What are the key skills and qualifications needed to thrive as a Causal Inference PhD Intern, and why are they important?

To thrive as a Causal Inference PhD Intern, you need a strong background in statistics, econometrics, and causal inference methods, often supported by advanced graduate studies in a related field. Familiarity with statistical programming languages such as R or Python, and experience using data analysis tools and frameworks like Stata or TensorFlow Probability, are typically required. Excellent problem-solving abilities, critical thinking, and the ability to communicate complex concepts clearly help you stand out in this role. These skills and qualities are crucial for designing robust experiments, drawing reliable conclusions, and effectively collaborating with interdisciplinary research teams.

What is the difference between Causal Inference Phd Internship vs Data Scientist Internship?

AspectCausal Inference Phd InternshipData Scientist Internship
Required CredentialsPhD in statistics, economics, or related fieldBachelor's or Master's in CS, statistics, or related field
Work EnvironmentResearch-focused, academic or industry research teamsData analysis, modeling, and business insights
Employer & Industry UsageResearch institutions, tech companies, financeTech firms, startups, finance, healthcare
Search & Comparison IntentFocus on causal inference research rolesBroader data analysis roles

While a Causal Inference Phd Internship emphasizes research in causal analysis with advanced credentials, a Data Scientist Internship covers broader data analysis skills suitable for various industries. Both roles involve working with data, but their focus, required background, and career paths differ significantly.

What is a Causal Inference PhD Internship?

A Causal Inference PhD Internship is a specialized research position for doctoral students focused on causal inference, which involves determining cause-and-effect relationships from data. Interns typically work with large datasets, advanced statistical models, and machine learning techniques to answer questions about how variables influence one another. These internships are often offered by tech companies, research labs, or policy organizations and provide hands-on experience in designing experiments, analyzing observational data, and developing new methodologies. The goal is to bridge academic research with real-world applications, contributing to projects that require rigorous causal analysis.
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Causal Inference Phd Internship jobs near you
Senior Data Scientist - Experimentation & Measurement

Senior Data Scientist - Experimentation & Measurement

PlayStation Global

San Mateo, CA • On-site

Other

Posted yesterday

Job description

Senior Data Scientist -  Experimentation & Measurement

San Mateo, CA

 Overview:

As a Senior Data Scientist on the Decision Science team within the Data Science, Analytics, & Enablement (DSAE) organization at PlayStation, you will take a leading role in designing and interpreting experiments that evaluate the impact of PS4 to PS5 user migration initiatives, growth marketing strategies, and broader campaign performance. This role is focused on advancing our experimentation practices-bringing statistical rigor, clear measurement strategies, and deep causal inference expertise to some of the most critical initiatives across PlayStation.

What You'll Be Doing:
  • Lead the design, execution, and interpretation of A/B tests and quasi-experiments to evaluate the impact of user migration initiatives (PS4 to PS5), growth marketing strategies, and campaign performance.
     
  • Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles.
     
  • Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results communication.
     
  • Apply advanced causal inference methods when experimentation isn't feasible or to inform test design and prioritization.
     
  • Help define and contribute to centralized experimentation frameworks, tools, and documentation to scale best practices across the company.
     
  • Independently extract, transform, and analyze data from complex systems using SQL, Python, and other analytics tools.
     
  • Communicate findings clearly to technical and non-technical stakeholders, helping drive business decisions with rigor and clarity.
     
  • Stay current on new methodologies in experimentation and causal analysis, and bring fresh perspectives to the team's work.
Basic Requirements:
 

  • Bachelor's degree or equivalent.
     

  • 5+ years of experience in a data science experimentation-focused role (3+ with PhD).
     

  • Deep expertise in A/B testing and causal inference, including quasi-experimental methods.
     

  • Proficiency in SQL for data extraction and transformation.
     

  • Proficiency in Python, including statistical and data science libraries.
     

  • Broad and applied knowledge of statistical techniques and machine learning modeling methods.
     

  • Proven ability to influence product and business decisions through clear, actionable insights.
     

  • Experience contributing to or developing experimentation frameworks, best practices, or internal tooling.

    Preferred Requirements:

  • Master's or PhD in Statistics, Economics, or Econometrics. Other degrees in quantitative disciplines may be considered.
     

  • Bonus: Interest in or knowledge of video games, gaming platforms, or player behavior.

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