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Phd Causal Inference Jobs (NOW HIRING)

Alembic

Research Engineer - Causal AI

San Francisco, CA · On-site

$200K - $250K/yr

Build production systems for causal inference that maintain statistical rigor at enterprise scale ... MS or PhD with significant applied research experience * Background in econometrics, statistics, or ...

YO AI Labs

Data Scientist

Glendale, CA

... PhD + 3 years of relevant experience with an emphasis on experimentation or causal inference. * Experience with ETL and data engineering: data extraction, transformation, integration, and quality ...

YO AI Labs

Data Scientist

Glendale, CA

... PhD + 3 years of relevant experience with an emphasis on experimentation or causal inference. * Experience with ETL and data engineering: data extraction, transformation, integration, and quality ...

airbnb, Inc.

$140 - $210/hr

... with a Phd degree. * Strong knowledge of causal inference, experimentation, applied statistical modeling, and end-to-end ML development. * Skilled in statistical programming (Python or R) and ...

New

Apple Inc.

Applied Scientist

Culver City, CA · On-site

$150 - $210/hr

Engineer end‑to‑end scalable and robust Causal Inference products which provide Apple with an ... PhD in related field. * Hands‑on experience leveraging Generative AI to improve productivity and ...

Apple

Applied Scientist

Austin, TX

$175K - $308K/yr

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 ...

Apple

Applied Scientist

Austin, TX

$175K - $308K/yr

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.

Machine Learning Engineer, Causal Inference, Level 5

Jobtailor

California, MO • On-site

$150 - $210/hr

Other

Posted 8 days ago

Job description

  • Design and build models that quantify causal impact, optimize decision‑making, and drive value for users, advertisers, and the business
  • Develop and productionize causal machine learning solutions (e.g., uplift modeling, heterogeneous treatment effect estimation) using observational and experimental data
  • Design, analyze, and interpret A/B tests and quasi‑experiments; collaborate closely with product and engineering partners to shape experimentation strategies
  • Evaluate technical tradeoffs between model complexity, bias/variance, scalability, and interpretability
  • Conduct code reviews, maintain high engineering standards, and build scalable, maintainable infrastructure
  • Contribute to rapid iteration cycles while ensuring methodological rigor
Requirements
  • Bachelor’s degree in computer science, statistics, economics, or a related technical field, or equivalent practical experience
  • 5+ years of post‑Bachelor’s experience in machine learning, with hands‑on experience in causal inference or experimentation; or Master’s degree in a technical field + 4+ years of post‑grad machine learning experience; or PhD in a relevant technical field + 2 years of post‑grad machine learning experience
  • Demonstrated experience building models to support product decision‑making and policy evaluation through causal techniques
  • Experience designing and analyzing online experiments (A/B tests) and leveraging causal ML in production systems
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