ZipRecruiter

Log In

1

Ai Causal Inference Jobs (NOW HIRING)

Intuit

Senior Staff AI Research Scientist

Mountain View, CA · On-site

$116K - $148K/yr

The team conducts applied and fundamental research across areas including decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems ...

Intuit

Senior Staff AI Research Scientist

Mountain View, CA · On-site

$116K - $148K/yr

The team conducts applied and fundamental research across areas including decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems ...

Intuit

Senior Staff AI Research Scientist

Mountain View, CA

$116K - $148K/yr

The team conducts applied and fundamental research across areas including decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems ...

Apple

Applied ML Science Manager

Cupertino, CA

$198K - $342K/yr

You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... AI to improve productivity and generate new insights Curious business attitude with an ability to ...

Apple

Applied Scientist

Austin, TX · On-site

You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... AI to improve productivity and generate new insightsCurious business attitude with an ability to ...

Ataraxis AI

Research Scientist

New York, NY · On-site

$120K - $210K/yr

About Ataraxis AI Ataraxis is an AI precision medicine company working at the intersection of multi ... causal inference and interpretability. * Translate machine learning and statistics papers into ...

Alembic

Senior Applied AI Engineer

San Francisco, CA · On-site

$182K - $207K/yr

... causal inference to deliver real-time analytics that were previously impossible. The Role We're ... The "AI" in Applied AI refers to the causal, graph-based, and neural systems our science team ...

Apple

Staff Data Scientist

Sunnyvale, CA

$203K - $305K/yr

... causal inference methodologies across large, complex data sets - Develop AI-native automated solutions to deliver prescriptive insights and proactive alerts - Drive the feature evaluation philosophy ...

next page

Showing results 1-20

All JobsAi Causal Inference Jobs

Ai Causal Inference information

See salary details

$16

$56

$81

How much do ai causal inference jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for ai causal inference in the United States is $56.81, according to ZipRecruiter salary data. Most workers in this role earn between $46.63 and $67.31 per hour, depending on experience, location, and employer.

What are AI Causal Inference professionals?

AI Causal Inference professionals specialize in using artificial intelligence and statistical methods to determine cause-and-effect relationships within data. Unlike traditional data analysts who may focus on correlations, these experts design experiments or apply mathematical models to uncover how changes in one variable influence another. Their work is crucial in fields like healthcare, economics, and social sciences, where understanding causality can inform better decisions and policies. They often use tools like causal diagrams, randomized controlled trials, and advanced machine learning techniques to draw robust conclusions.

What are the key skills and qualifications needed to thrive as an AI Causal Inference Specialist, and why are they important?

To thrive as an AI Causal Inference Specialist, you need a strong background in statistics, machine learning, and causal modeling, typically supported by an advanced degree in a quantitative field. Familiarity with programming languages like Python or R, experience with causal inference libraries (such as DoWhy or CausalNex), and knowledge of statistical software are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret complex results and collaborate across multidisciplinary teams. These skills ensure accurate causal analysis, actionable insights, and reliable decision-making in data-driven environments.

What are some common challenges faced by professionals working in AI causal inference, and how can they be addressed?

Professionals in AI causal inference often encounter challenges such as dealing with incomplete or biased data, distinguishing correlation from true causation, and communicating complex findings to non-technical stakeholders. Addressing these challenges typically involves leveraging robust statistical methods, collaborating closely with domain experts, and maintaining transparency in modeling decisions. Continuous learning and staying updated with the latest research can also help navigate the rapidly evolving landscape of AI causal inference.
Infographic showing various Ai Causal Inference job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 3% Full Time, and 96% Part Time. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $118,171 per year, or $56.8 per hour.
Postdoctoral Fellow in Biostatistics and Health Data Science

Postdoctoral Fellow in Biostatistics and Health Data Science

Indiana University

Bloomington, IN • On-site

$45K - $61K/yr

Full-time

Posted 18 days ago

Job description

Posting Details
Position Details
Title
Postdoctoral Fellow in Biostatistics and Health Data Science
Specific Title
Appointment Type
Postdoctoral Fellow
Department
IUSM - Biostatistics
Campus
IU School of Medicine Indianapolis
Position Summary
Postdoctoral Researcher to advance research at the intersection of artificial intelligence for healthcare, multimodal data analysis (EHRs, medical imaging, omics, physiological signals, clinical notes), and causal AI (causal inference, discovery, counterfactual reasoning). The successful candidate will collaborate with an interdisciplinary team of computer scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations.
Key responsibilities include:
  • Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines.
  • Build reproducible research pipelines and maintain reliable experiment codebases (prefer Python).
  • Apply causal inference and discovery frameworks to clinical questions.
  • Translate proposed methods and frameworks into real-world clinical workflows.
  • Contribute to grant proposals and research reports.

This is an exciting opportunity to join a fast growing BHDS Department with 36 faculty members and more than 50 professional staff. We are dedicated to excellence in biostatistical, health data science, and informatics research and education. We have an extensive portfolio of research program in related areas. Our NIH funding as principal investigators and co-investigators has been ranked among the top in the nation. The Department currently has an ongoing PhD program in Biostatistics, MS program in Biostatistics, and BS program in Health Data Science.
We have established strong collaborations with both clinical and basic science research departments and divisions and health systems including IU Health and Eskenazi Hospitals as well as strong partnerships with major research institutes and centers including Regenstrief Institute, Center for Computational Biology and Bioinformatics, Indiana Clinical and Translational Science Institute (CTSI), Indiana University Simon Comprehensive Cancer Center, Indiana Institute of Biomedical Research, and Indiana Alzheimer's Disease Research Center. Additional details about the Department and the PhD program are available on our web page: https://medicine.iu.edu/biostatistics.
The Indianapolis Campus is the focal point of health professions education at Indiana University, and the School of Medicine is the country's second largest allopathic medical school. Indianapolis consistently ranks high nationally on many of the "best places to live" lists and has an economy that is growing in the life sciences arena. In addition, it has always been one of the cities with the lowest cost of living. Carmel, Indy's northern neighbor, was recently named as the best mid-sized city in the country.
IUSM is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all throughout the state of Indiana.
Indianapolis is the capital and most populous city in the State of Indiana. It is growing economically thanks to a strong corporate base anchored by the life sciences. Indiana is home to one of the largest concentrations of health sciences companies in the nation. Indianapolis has a sophisticated blend of charm and culture with a wonderful balance of business and leisure. The growing residential base is supported by rich amenities and quality of life - the city possesses a variety of professional sports, arts venues and outdoor recreation areas. Residents of this dynamic city, and surrounding suburbs, enjoy leading educational systems and top-ranked universities, paired with a diverse population. Indianapolis International Airport is a top-ranked international airport, being named "Best Airport in North America" by Airports Council International for many years. For additional information on life in Indy: https://faculty.medicine.iu.edu/relocationThe search will continue until the positions are filled.
Basic Qualifications
Required Qualifications:
  • Ph.D. (by start date) in Computer Science, Biomedical Informatics, Health Data Science, Biostatistics, or a closely related area.
  • Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP.
  • Demonstrated working experience with healthcare data (e.g., EHR, clinical text, imaging, omics).
  • Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g., Weights & Biases).
  • Excellent written and oral communication skills, and ability to collaborate with multidisciplinary teams.

Preferred Qualifications:
  • Experience with LLMs/foundation models (e.g., clinical NLP, retrieval-augmented generation, instruction tuning) and multimodal transformers.
  • Solid understanding of causal methods (e.g., propensity scores, IPW, matching) and/or causal discovery.
  • Familiarity with data engineering and MLOps (e.g., SQL, Spark, Airflow, Docker, Kubernetes).
  • Knowledge of responsible/ethical AI for health: fairness/equity, interpretability, robustness, privacy (e.g., differential privacy, federated learning).
  • Track record of first-author publications in relevant venues and collaborative open-source contributions.

Department Contact for Questions
Professor Jiang Bian via email at: bianj@regenstrief.org
Additional Qualifications
Special Instructions
Priority Application Review Deadline
Expected Start Date
Posting Number
IUSM-02286-2025

Apply