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Phd Causal Inference Jobs (NOW HIRING)

Roku, Inc.

Sr. Research Data Scientist

Boston, MA · On-site

$330 - $375/hr

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 ...

New

Roku

Senior Research Data Scientist

Boston, MA

$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 ...

Roku

Senior Research Data Scientist

San Jose, CA

$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 ...

Roku

Senior Research Data Scientist

New York, NY

$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 ...

Twitch

Data Scientist

San Francisco, CA

OR a PhD in Economics, Statistics, Computer Science, or related quantitative field * Proficiency in SQL * Proficiency with Python or R * Strong foundation in experimentation and causal inference ...

Twitch

Data Scientist

New York, NY · On-site

OR a PhD in Economics, Statistics, Computer Science, or related quantitative field * Proficiency in SQL * Proficiency with Python or R * Strong foundation in experimentation and causal inference ...

Expedia, Inc.

Senior Economist

Seattle, WA · On-site

$130 - $160/hr

Partner with ML teams to integrate causal inference into production systems, informing ranking ... PhD in Economics, Applied Economics, Econometrics, Statistics, or a related quantitative field ...

Twitch

Data Scientist

Seattle, WA · On-site

OR a PhD in Economics, Statistics, Computer Science, or related quantitative field * Proficiency in SQL * Proficiency with Python or R * Strong foundation in experimentation and causal inference ...

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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Phd Causal Inference information

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$40K

$122.9K

$178.5K

How much do phd causal inference jobs pay per year?

As of Aug 20, 2026, the average yearly pay for phd causal inference in the United States is $122,928.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,000.00 and $138,000.00 per year, depending on experience, location, and employer.

What is a PhD in causal inference?

A PhD in Causal Inference is an advanced research degree focused on understanding and identifying cause-and-effect relationships using statistical and computational methods. Students in this field learn to design studies, analyze data, and develop new methodologies to answer complex causal questions in areas such as social sciences, medicine, economics, and artificial intelligence. Graduates often work in academia, research institutions, or industries where evidence-based decision-making is essential.

What are the key skills and qualifications needed to thrive as a PhD causal inference researcher?

To thrive as a PhD Causal Inference researcher, you need advanced knowledge of statistics, econometrics, and causal modeling, typically supported by a doctoral degree in a quantitative field. Familiarity with statistical programming languages (such as R or Python), specialized software (like STATA or SAS), and experience with experimental or quasi-experimental methods are essential. Strong analytical thinking, attention to detail, and the ability to communicate complex findings clearly make a candidate stand out. These skills ensure rigorous, credible research that can inform policy, product development, or scientific understanding by accurately identifying causal relationships.

What collaborative opportunities can a PhD specializing in causal inference expect within a multidisciplinary research team?

PhD professionals in Causal Inference frequently collaborate with experts from fields such as epidemiology, economics, computer science, and public health. They often work closely with data scientists, subject matter experts, and statisticians to design studies, interpret complex datasets, and develop robust analytical models. This multidisciplinary environment fosters continuous learning and often leads to co-authorship on research publications, participation in grant writing, and involvement in high-impact policy or product decisions. Effective communication and teamwork skills are essential to translate technical findings for diverse audiences and drive actionable insights.
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Phd Causal Inference jobs near you
Infographic showing various Phd Causal Inference job openings in the United States as of August 2026, with employment types broken down into 77% Full Time, 21% Part Time, and 2% Contract. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution, with an average salary of $122,928 per year, or $59.1 per hour.

Principal Research Data Scientist

Jobtailor

San Francisco, CA • On-site

$120 - $180/hr

Other

Re-posted 12 hours ago

Job description

Responsibilities
  • Own research projects end-to-end, from study design through analysis, interpretation, and publication.
  • Design and run observational and quasi-experimental studies on real-world hospital data.
  • Analyze complex clinical and operational datasets and stand behind the methods.
  • Collaborate with frontline clinicians, health system executives, customer success, go-to-market, and data science teams to develop new research questions, weigh in on product decisions, and lead outcomes and impact studies tied to health system partnerships.
Requirements
  • PhD in statistics, biostatistics, epidemiology, or a related field.
  • At least 2 years of (non-PhD) experience conducting observational health research using large healthcare databases.
  • Background in epidemiology or outcomes research.
  • Deep expertise in causal inference on observational data: difference-in-differences, regression discontinuity, interrupted time series, propensity methods.
  • Fluency in Python, including the ability to wrangle large, observational clinical datasets.
  • A track record of owning analyses or full research projects independently.
Core Competencies

Demonstrates expertise in designing and conducting observational health research, with a strong focus on causal inference methods and the ability to analyze complex clinical datasets using Python. Proven track record of leading research projects from inception to publication while collaborating effectively with diverse teams.

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