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Phd Causal Inference Jobs in Boston, MA (NOW HIRING)

Pfizer

Senior Computational Geneticist

Cambridge, MA · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... discovery, causal inference, biological interpretation, biomarker identification, and patient ... PhD required and post-doctoral experience in genetics, statistical genetics, or genetic ...

New

NorthEastern

Postdoctoral Research Fellow

Boston, MA

$60K - $85K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Doctoral degree (PhD) in Epidemiology, Environmental Health, Biostatistics, Child Development ... Knowledge of causal inference methods (e.g., propensity score analysis, directed acyclic graphs ...

XPO Logistics

Senior Scientist, Data Science - Hybrid

Boston, MA · On-site

$106K - $132K/yr

  • Medical

  • Life

  • Retirement

  • PTO

A Master's or PhD in Computer Science, AI, Data Science, or a related quantitative field * years of ... Experience with causal inference and measurement methods for analyzing the impact of pricing ...

Socket.dev

Data Scientist I

Somerville, MA · On-site

$140 - $170/hr

... causal inference. * Practical data skills: experience with Python, pandas, and SQL, with the ... MS or PhD) These are what we are looking for, not a rigid checklist. Candidates who are still ...

Northeastern University

Postdoctoral Research Fellow

Boston, MA · On-site

$60K - $85K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Doctoral degree (PhD) in Epidemiology, Environmental Health, Biostatistics, Child Development ... Knowledge of causal inference methods (e.g., propensity score analysis, directed acyclic graphs ...

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Phd Causal Inference information

See Boston, MA salary details

$43.5K

$133.5K

$193.9K

How much do phd causal inference jobs pay per year?

As of Aug 14, 2026, the average yearly pay for phd causal inference in Boston, MA is $133,549.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $149,900.00 per year, depending on experience, location, and employer.

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

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.

What are popular job titles related to Phd Causal Inference jobs in Boston, MA?

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Phd Causal Inference jobs near you
Infographic showing various Phd Causal Inference job openings in Boston, MA as of August 2026, with employment types broken down into 82% Full Time, 14% Part Time, and 4% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $133,549 per year, or $64.2 per hour.

Postdoctoral Fellow in Biomedical Informatics (Cai Lab)

Harvard University

Cambridge, MA • On-site

$54K - $73K/yr

Full-time

Re-posted 25 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

80th of 618 rated colleges and universities

Job description

Position
Details
Title
Postdoctoral Fellow in Biomedical Informatics (Cai Lab)
School
Harvard Medical School
Department/Area
Biomedical Informatics
Position Description
A Postdoctoral Research Fellow position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic research group focused on several synergistic goals: generating actionable Real-World Evidence (RWE) from multi-institutional Electronic Health Records (EHR), improving the generalizability of clinical evidence across diverse populations using multi-source and multi-modal data, and accelerating drug discovery by leveraging these rich, integrated datasets. This role offers a unique opportunity to develop methodological innovations that bridge the gap between computational theory and impactful clinical application.
We are seeking a highly motivated individual with a strong statistical and machine learning background. The ideal candidate will have existing expertise in several of the following areas, aligned with our research focus: 1) Causal inference, invariant learning and representation learning; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing.
Basic Qualifications
Candidates must hold a Ph.D. in a quantitative field, such as statistics, biostatistics, computer science, or a related discipline. Success in this position requires strong quantitative research capabilities and demonstrated proficiency in programming, specifically in Python and R, as well as experience with modern deep learning frameworks like PyTorch or TensorFlow. In addition to technical skills, the candidate must possess excellent written and oral communication abilities to effectively disseminate research findings and collaborate within a multidisciplinary team.
Additional Qualifications
Special Instructions
Contact Information
Mo Moro
Contact Email
mohammed_moro@hms.harvard.edu
Salary Range
Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, can be found at https://postdoc.hms.harvard.edu/guidelines
Minimum Number of References Required
Maximum Number of References Allowed
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