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Causal Inference Jobs in Columbia, MD (NOW HIRING)

2U

Data Scientist II

Washington, DC · On-site +1

Experimentation and causal inference Own A/B tests end-to-end, from design and power analysis through interpretation. Where randomization isn't possible, use quasi-experimental methods such as ...

MELE Associates

Data Evaluator/Analyst

Washington, DC · On-site +1

$100/hr

Apply econometrics and statistical modeling, including regression analysis, panel data methods, and causal inference techniques. * Develop analytic frameworks linking facility usage to downstream ...

Umd

Senior Faculty Specialist

College Park, MD

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

Mele Accociates

Data Evaluator/Analyst

Washington, DC · On-site

$100K - $110K/yr

Apply econometrics and statistical modeling, including regression analysis, panel data methods, and causal inference techniques. * Develop analytic frameworks linking facility usage to downstream ...

ADVI Health LLC

Biostatistician I

Washington, DC · On-site

$112K - $140K/yr

Day to day, you will design, execute, and document analyses with a strong emphasis on causal inference methods, while developing and owning complex statistical analysis plans from inception to ...

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Causal Inference information

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$54.6K

$98.5K

$134.5K

How much do causal inference jobs pay per year?

As of Jul 27, 2026, the average yearly pay for causal inference in Columbia, MD is $98,477.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,300.00 and $107,700.00 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.

What job categories do people searching Causal Inference jobs in Columbia, MD look for? The top searched job categories for Causal Inference jobs in Columbia, MD are:
What cities near Columbia, MD are hiring for Causal Inference jobs? Cities near Columbia, MD with the most Causal Inference job openings:
Causal Inference jobs near you
Infographic showing various Causal Inference job openings in Columbia, MD as of July 2026, with employment types broken down into 87% Full Time, 12% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $98,477 per year, or $47.3 per hour.
Postdoctoral Fellowship Opening: Statistical Methods for Health Policy

Postdoctoral Fellowship Opening: Statistical Methods for Health Policy

Johns Hopkins University

Baltimore, MD • On-site

$48K - $66K/yr

Full-time

Posted 3 days ago

Johns Hopkins Medicine rating

7.5

Company rating: 7.5 out of 10

Based on 205 frontline employees who took The Breakroom Quiz

230th of 890 rated healthcare providers

Job description

Description
Postdoctoral Fellowship opening to work on applied causal inference, and especially statistical approaches for studying health policy, under the direction of Dr. Elizabeth Stuart and in collaboration with researchers at Weill Cornell conducting evaluations of mental health policies and services.
Projects will include policy evaluation methods and application, including through the use of large-scale claims and other health care data. Strong candidates also have a strong interest in the translation and dissemination of statistical methods to broad audiences.
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 (especially policy evaluation approaches) 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.
Questions about the position can be directed to Dr. Stuart (https://www.elizabethstuart.org/; estuart@jhu.edu).
Qualifications
  • PhD in Biostatistics, Statistics, Economics, Epidemiology, Health Policy, or a related quantitative field
  • Strong methodological and computational skills
  • Strong written and oral communication skills
  • Ability to work collaboratively with interdisciplinary teams

Application Instructions
Interested applicants should submit the following materials via Interfolio:
  • Cover letter expressing interest and fit for the position
  • Curriculum vitae
  • Contact information for three references

Application review will begin September 1, and applications will be considered until the position is filled. The start date is flexible, from November 2026 and beyond. The initial appointment is for one year, with reappointment for a second year provided satisfactory performance.

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