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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 * Develop algorithms that are both mathematically sound and computationally efficient * Collaborate ...

Apple

Applied Scientist

Austin, TX · On-site

$171K - $302K/yr

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

Apple

Applied Scientist

Austin, TX

$171K - $302K/yr

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

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 solutions, that directly impact our products and provide a granular understanding of key business ...

PlayStation Global

OR · On-site

Design, execute, and interpret A/B tests and quasi-experiments, and apply advanced causal inference methods when experimentation isn't feasible. * Partner with cross-functional teams (product ...

Apple

Applied Scientist

Austin, TX · On-site

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

Intuit

Senior Data Scientist

San Diego, CA

Causal Inference: Lead causal inference and econometric analyses to understand and influence key levers of business growth with a crisp understanding of incremental impact. Metric Design & Impact ...

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Causal Inference information

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$55K

$99.2K

$135.5K

How much do causal inference jobs pay per year?

As of Jun 20, 2026, the average yearly pay for causal inference in the United States is $99,231.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,000.00 and $108,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Causal Inference position, and why are they important?

Success in a Causal Inference role requires strong statistical knowledge, expertise in experimental and quasi-experimental methodologies, and advanced proficiency in programming languages like R or Python, typically acquired with an advanced degree in statistics, economics, data science, or a related field. Familiarity with specialized statistical software (such as Stata, SAS, or causal inference packages in R/Python), as well as experience with large datasets and machine learning tools, is highly valued. Excellent problem-solving abilities, clear communication, and collaboration skills are essential soft skills for effectively conveying complex findings to diverse teams. These competencies are critical to producing reliable insights that guide evidence-based decision-making in business, healthcare, or policy settings.

What are some common challenges faced in a Causal Inference position?

Professionals in Causal Inference often encounter challenges such as dealing with confounding factors, addressing selection bias, and ensuring the validity of assumptions behind statistical models. They must carefully design experiments or leverage observational data while staying vigilant about potential data quality issues and model limitations. Collaboration with subject matter experts, data engineers, and business stakeholders is common to ensure accurate contextualization of results. Overcoming these challenges requires a mix of technical acumen and strong communication skills to translate complex analyses into actionable recommendations.

What is a Causal Inference job?

A Causal Inference job involves using statistical and computational methods to determine cause-and-effect relationships from data. Professionals in this field work with observational and experimental data to identify causal impacts, often in domains like economics, healthcare, social sciences, and technology. They apply techniques such as propensity score matching, instrumental variables, and difference-in-differences to ensure rigorous analysis. These roles are commonly found in academia, policy research, and data science teams within tech and finance companies. Strong skills in statistics, programming (e.g., Python, R), and experimental design are typically required.

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What cities are hiring for Causal Inference jobs? Cities with the most Causal Inference job openings:
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Causal Inference jobs near you
Infographic showing various Causal Inference job openings in the United States as of June 2026, with employment types broken down into 91% Full Time, and 9% Part Time. Highlights an 73% In-person, 3% Hybrid, and 24% Remote job distribution, with an average salary of $99,231 per year, or $47.7 per hour.
Adjunct Instructor in Statistical Modeling and Causal Inference

Adjunct Instructor in Statistical Modeling and Causal Inference

Brandeis University

Waltham, MA • On-site

$6.5K/mo

Part-time

Posted yesterday

Job description

Brandeis University's Online Applied Data Science and Decision Analytics Program is seeking an Adjunct Faculty member for RADS 105 Statistical Modeling and Causal Inference for the Fall 1 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Applied Data Science and Decision Analytics.
This course will cover regression, identification strategies, and causal inference techniques for evaluation of programs, products, and policies.
Core Course Responsibilities Summary:
  • Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.
  • Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.
  • Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.
  • Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.

Qualifications:
  • Required:
    • Advanced degree (MS or Ph.D.) in Statistics, Biostatistics, Applied Mathematics,Data Science or a related field.
    • Experience in statistical modeling and causal inference, including regression analysis, identification strategies, and methods for addressing bias and confounding in observational data. Ability to apply models to real-world program, product, or policy evaluation contexts.
    • Professional experience building regression, generalized linear models, hierarchical/multilevel models, and Bayesian approaches
    • The ability to apply models to real-world datasets and to incorporate statistical software such as SPSS.
    • At least 1 year of teaching or training experience (preferably online/asynchronous)
    • Experience with online instruction
    • Excellent communication and teaching skills in an online learning environment.
  • Preferred:
    • Prior online teaching experience at the graduate level
    • Knowledge of global learner personas and culturally responsive pedagogy
    • Familiarity with Moodle LMS and digital authoring tools (e.g., H5P)

Interested candidates should submit:
A cover letter highlighting relevant qualifications and teaching experience.
A current CV or resume.
Contact information for three professional references.
Application review begins May 27, 2026 though we will continue to accept submissions on an ongoing basis.
This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.
Compensation for this position is $6573.15
Pay Range Disclosure
The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.
Equal Opportunity Statement
Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").

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