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Phd Causal Inference Jobs (NOW HIRING)

Intuit

Staff Data Scientist

Mountain View, CA

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Qualifications Master's or PhD degree in Computer Science, Statistics, Econometrics, Data Science ...

Lennar

Lead Data Scientist

Boston, MA

Design and run experiments (A/B tests, multi-armed bandits, uplift modeling, causal inference) and ... Advanced degree (MS/PhD) preferred. * 7+ years of applied data science experience (5+ with MS, 3+ ...

Apple

Applied ML Science Manager

Cupertino, CA · On-site

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

Intuit

Staff Data Scientist

Mountain View, CA

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Qualifications Master's or PhD degree in Computer Science, Statistics, Econometrics, Data Science ...

Expedia

Senior Economist

Seattle, WA

$277K/yr

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 * 8+ ...

New

Lennar Homes

Lead Data Scientist

Boston, MA

Design and run experiments (A/B tests, multi-armed bandits, uplift modeling, causal inference) and ... Advanced degree (MS/PhD) preferred. 7+ years of applied data science experience (5+ with MS, 3+ ...

Intuit

Staff Data Scientist

San Diego, CA · On-site

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Qualifications Master's or PhD degree in Computer Science, Statistics, Econometrics, Data Science ...

Lennar

Lead Data Scientist

Boston, MA · On-site +1

Design and run experiments (A/B tests, multi-armed bandits, uplift modeling, causal inference) and ... Advanced degree (MS/PhD) preferred. * 7+ years of applied data science experience (5+ with MS, 3+ ...

Intuit

Staff Data Scientist

San Diego, CA · On-site

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Qualifications Master's or PhD degree in Computer Science, Statistics, Econometrics, Data Science ...

Lyft

Data Science Manager, Mapping

San Francisco, CA · On-site

Ensure robust experimentation and causal inference methodologies are applied to measure the impact ... Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research ...

Grubhub

Senior Staff Data Scientist

Chicago, IL

Develop causal inference and experimentation frameworks that help Wonder understand which product ... What You Bring to the Table * 8+ years of industry experience with MS or 6+ years with PhD in ...

Grubhub

Senior Staff Data Scientist

New York, NY

Develop causal inference and experimentation frameworks that help Wonder understand which product ... What You Bring to the Table * 8+ years of industry experience with MS or 6+ years with PhD in ...

Gopuff

Senior Data Scientist - Delivery Technology

... causal inference to measure the impact of our models on user engagement and business metrics. Qualifications : Required : • MS or PhD in Operations Research, Mathematics, Statistics, Economics ...

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How much do phd causal inference jobs pay per year?

As of Jun 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 are the key skills and qualifications needed to thrive as a PhD Causal Inference researcher, and why are they important?

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.

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.
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Postdoctoral Fellow - Biostatistics

Postdoctoral Fellow - Biostatistics

MD Anderson

Houston, TX

$64K - $76K/yr

Full-time

Medical, Dental, Retirement, PTO

Posted 14 days ago

MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 164 frontline employees who took The Breakroom Quiz

33rd of 873 rated healthcare providers

Job description

The Department of Biostatistics at has one postdoctoral fellow position open for biostatistics and data science methodology research in clinical trials. The main focus is research and publication. The primary focus will be to develop novel methods for causal AI/inference methods, adaptive Bayesian clinical trial designs, derive related statistical theory, produce software for implementation, incorporate biomarkers in clinical trial design and analysis, and build statistical learning tools for large data sets. The postdoctoral fellow will work under the supervision of Dr. Liang on challenging and important clinical and biological projects that involve complex statistical modeling, data analysis, and computation.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
Trainee will learn through various research projects, with a primary focus on: (1) developing novel statistical and data science methods, as well as user-friendly software, for integrating AI tools to evaluate novel treatments or design future clinical trials in overall population or subgroups, and (2) analyzing real-world and institutional medical datasets. A major methodological focus will be integrating machine learning/artificial intelligence tools, causal inference methods, Bayesian techniques, and adaptive designs to build innovative, next-generation tools for adaptively and efficiently evaluating treatment effectiveness and learning optimal treatment decisions that may vary by different patients' subgroups.
ELIGIBILITY REQUIREMENTS
Applicants must have a recent PhD in biostatistics or statistics from a reputed University/Institute or within 0-1 years of graduation. At least one first author publication in a peer reviewed journal stemming from PhD studies is required. Candidates must have strong methodological training in statistics or biostatistics, especially in causal inference or semiparametric methods, and have strong computer programming skills, in particular using R or Python. Expertise or skills in the following areas are highly desirable: Causal inference, double/debias machine learning, semiparametric methods, Bayesian MCMC computational methods, adaptive clinical trials, and machine learning for estimation or decision-making.
Please send CV and information on three referees directly to mliang2@mdanderson.org.
POSITION INFORMATION
MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000. depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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