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Causal Inference Jobs in Baltimore, MD (NOW HIRING)

Umd

Senior Faculty Specialist

College Park, MD · On-site

Familiarity with experimental design and causal inference methodologies *Familiarity with or interest in applying generative AI techniques *Excellent communication skills, passion for educational ...

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How much do causal inference jobs pay per year?

As of May 29, 2026, the average yearly pay for causal inference in Baltimore, MD is $98,600.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,500.00 and $107,800.00 per year, depending on experience, location, and employer.

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.

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.
More about Causal Inference jobs
What are the most commonly searched types of Causal Inference jobs in Baltimore, MD? The most popular types of Causal Inference jobs in Baltimore, MD are:
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What job categories do people searching Causal Inference jobs in Baltimore, MD look for? The top searched job categories for Causal Inference jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Causal Inference jobs? Cities near Baltimore, MD with the most Causal Inference job openings:
Causal Inference jobs near you
Infographic showing various Causal Inference job openings in Baltimore, MD as of May 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $98,600 per year, or $47.4 per hour.
Postdoctoral Fellowship Opening: Applied Causal Inference for the Social and Behavioral Sciences

Postdoctoral Fellowship Opening: Applied Causal Inference for the Social and Behavioral Sciences

Johns Hopkins University

Baltimore, MD • On-site

$48.70K - $66.10K/yr

Full-time

Posted 19 days ago

Johns Hopkins Medicine rating

7.5

Company rating: 7.5 out of 10

Based on 199 frontline employees who took The Breakroom Quiz

216th of 864 rated healthcare providers

Job description

Description
Postdoctoral fellowship opening to work on applied causal inference under the direction of Dr. Elizabeth Stuart, in collaboration with Dr. Beth McGinty and colleagues at Johns Hopkins and Weill Cornell. Projects will include policy evaluation methods and application, and methods of relevance for implementation science and the work of the ALACRITY Center for Health and Longevity in Mental Illness. Strong candidates also have a strong interest in teaching causal inference topics to broad audiences, including potential development of short courses and other trainings to introduce causal inference topics to individuals without a methodological background. Work will include methods development as well as applications of advanced statistical methods in public health and medicine, and will involve collaboration with other faculty in Biostatistics and the School of Public Health. A key focus of the work will be collaboration with researchers at Weill Cornell conducting evaluations of mental health policies and services.
Responsibilities will include statistical collaboration, methods development, methodological literature reviews, simulation studies, educational activities, data management and analyses, manuscript writing for journal publications, and presentations at scientific meetings. Individuals with training in quantitative methods, including Statistics, Biostatistics, Economics, Epidemiology, and Health Policy are welcome to apply. Knowledge of causal inference methods and experience with statistical software such as Stata or R is required. Applicants will join a collegial and interdisciplinary team, and communication and collaboration skills are highly valued.
Successful candidates will receive competitive salaries (in the range $65,000-$75,000), as well as computing resources, travel support, and other benefits in accordance with departmental and university policies. Application review will begin February 1, and applications will be considered until the position is filled. The position can start any time from April to September 2026. The initial appointment is for one year, with reappointment for a second year provided satisfactory performance.
Qualifications
PhD in biostatistics, statistics, economics, health policy, health economics, or other quantitative field
Application Instructions
Interested applicants should submit the following materials via Interfolio:
• Cover letter
• Curriculum vitae
• 2 reference letters
Questions about the position can be directed to Dr. Stuart (https://www.elizabethstuart.org/; estuart@jhu.edu).

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