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Remote Causal Inference Jobs in Chicago, IL (NOW HIRING)

Product Data Analyst

Chicago, IL · Remote

$145K - $175K/yr

Causal inference methods (diff-in-diff, regression discontinuity, propensity matching) * Prior work ... Experience building metrics frameworks or KPI hierarchies from scratch How we work Fully remote ...

Stay current with the latest methodological advances in RWE, including causal inference and ... Additionally, for remote roles open to individuals in unincorporated Los Angeles - including remote ...

Remote Causal Inference information

See Chicago, IL salary details

$17

$58

$83

How much do remote causal inference jobs pay per hour?

As of Jun 22, 2026, the average hourly pay for remote causal inference in Chicago, IL is $58.53, according to ZipRecruiter salary data. Most workers in this role earn between $48.03 and $69.33 per hour, depending on experience, location, and employer.

What is a Remote Causal Inference job?

A Remote Causal Inference job involves using statistical and analytical methods to determine cause-and-effect relationships from data, often for fields like healthcare, social sciences, or business. Professionals in this role work remotely, leveraging tools such as R, Python, or specialized software to analyze experiments, observational studies, or large datasets. Their insights help organizations make data-driven decisions, design better interventions, and accurately measure the impact of policies or treatments. Strong skills in statistics, machine learning, and communication are essential for success in this position.

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

To thrive as a Remote Causal Inference Specialist, you need strong quantitative and statistical skills, a solid background in econometrics or data science, and typically an advanced degree in a related field. Proficiency with statistical programming languages such as R or Python, experience with causal inference frameworks like propensity score matching or instrumental variables, and familiarity with data visualization tools are crucial. Outstanding problem-solving abilities, clear communication, and self-motivation are essential soft skills for working independently and conveying complex results to non-technical stakeholders. These skills enable accurate, actionable insights from data, which drive evidence-based decision-making in remote, collaborative environments.

How does a remote Causal Inference specialist typically collaborate with cross-functional teams, and what tools are commonly used?

As a remote Causal Inference specialist, you’ll frequently work with data scientists, product managers, and engineers to design and interpret experiments, analyze observational data, and provide actionable insights. Collaboration usually happens through regular video meetings, shared documentation, and project management tools. Commonly used platforms include Slack or Microsoft Teams for communication, GitHub for code collaboration, and Jupyter Notebooks or RMarkdown for sharing reproducible analyses. These tools help ensure transparency and maintain strong teamwork despite the remote environment.
What are the most commonly searched types of Causal Inference jobs in Chicago, IL? The most popular types of Causal Inference jobs in Chicago, IL are:
What are popular job titles related to Remote Causal Inference jobs in Chicago, IL? For Remote Causal Inference jobs in Chicago, IL, the most frequently searched job titles are:
What cities near Chicago, IL are hiring for Remote Causal Inference jobs? Cities near Chicago, IL with the most Remote Causal Inference job openings:
Statistical Analyst (Remote Eligible)

Statistical Analyst (Remote Eligible)

Mathematica

Chicago, IL • On-site, Remote

$70K - $90K/yr

Full-time

Posted 17 days ago


Job description

Statistical Analyst (Remote Eligible)
About Mathematica:
Mathematica applies expertise at the intersection of data, methods, policy, and practice to improve well-being around the world. We collaborate closely with public- and private-sector partners to translate big questions into deep insights that improve programs, refine strategies, and enhance understanding using data science and analytics. Our work yields actionable information to guide decisions in wide-ranging policy areas, from health, education, early childhood, and family support to nutrition, employment, disability, and international development.
Mathematica offers our employees competitive salaries and a comprehensive benefits package, as well as the advantages of being 100 percent employee owned. As an employee stock owner, you will experience financial benefits of ESOP holdings that have increased in tandem with the company's growth and financial strength. You will also be part of an independent, employee-owned firm that is able to define and further our mission, enhance our quality and accountability, and steadily grow our financial strength.
Read more about our benefits here: Benefits at a Glance.
At Mathematica, we take pride in our commitment to diversity. Building an inclusive culture that draws on the individual strengths of employees from different ethnic backgrounds, cultures, lifestyles, abilities, and experience is key to our success.
We are seeking a masters-level Statistical Analyst to join our vibrant group of over 20 statisticians and data scientists. The contributions of our statisticians and statistical analysts underpin our ability to produce crucial evidence for policy and decision makers, ultimately furthering our mission to improve public well-being. For example, our statistical analysts have contributed to projects developing COVID-19 decision tools, extending state-of-the-art methods for identifying treatment effect heterogeneity to enhance primary care delivery, and leveraging Bayesian factorial design to improve the presentation of school choice information to low-income parents.
As part of their employment, statistical analysts benefit from the mentorship of more senior statisticians and subject-matter experts, learning new techniques and familiarizing themselves with new topic areas through involvement in analyses.
Responsibilities:
Analysis:
  • Apply statistical and quantitative methods to evaluate and improve social programs and policies, with the oversight of more senior statisticians. Assist in designing rigorous studies, determining appropriate analytic methods, selecting survey samples, calculating nonresponse adjustments, analyzing survey responses, and interpreting findings.

Programming:
  • Write programs to perform all stages of quantitative analysis, including: (1) conduct data extraction, cleaning, and manipulation, (2) apply advanced statistical and quantitative techniques appropriate for both survey and administrative data, and (3) develop programs to calculate descriptive statistics, populate tables, and visualize results.

Communication:
  • Draft sections of reports, including technical appendices, and presentations for colleagues, policymakers and other stakeholders. Communicate findings to internal project teams via memos, presentations, or markdown files.

Required Qualifications:
  • Master's degree with quantitative discipline, such as statistics, biostatistics, applied mathematics, quantitative economics, survey methodology, data science, or a related field, or an equivalent combination of education and experience
  • Coursework or experience in some of the following statistical and/or quantitative methods: causal inference at both the design (matching or weighting for comparison group selection) and analysis (regression) phases, experimental design, Bayesian inference, hierarchical/multilevel modeling, longitudinal data analysis, performance measurement, SEIR modeling, spatial statistics, small area estimation, survey sampling, non-response weighting, power calculation, and predictive modeling
  • Fluency in one or more of the following statistical programming languages: R (preferred), Python, Stan, Julia, Stata, or SAS
  • Excellent written and oral communication skills, including an ability to translate statistical methods and findings for a non-technical audience

Preferred:
  • Experience contributing to written deliverables, such as proposals, technical reports, or academic manuscripts
  • Background or interest in social policy research and a focus on health policy research

This position offers an anticipated annual base salary range of $70,000 to $90,000.
To apply, please submit cover letter, resume, location preferences, salary requirements, and code samples via our careers page. Please include a code sample (or two or three) which best represents your programming skills, preferably in R. If you include a GitHub, please call out the specific samples you want to highlight. If you do not have code available in these preferred languages, please send a code sample in an alternate language.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, age, national origin, religion, orientation, gender identity, status as a veteran, and basis of disability or any other federal, state, or local protected class.
At Mathematica, we understand the importance of building relationships with colleagues. If you're not located near one of our offices but would like opportunities to meet up with co-workers, we offer coworking spaces where available. Ask your Talent Acquisition partner for more information about this opportunity and whether it's an option in your area.
Any offer of employment will be contingent upon passing a background check. Various federal agencies with whom we contract require that staff successfully undergo security clearance as a condition of working on the project. If you are assigned to such a project, you will be required to obtain the requisite security clearance. Additionally, if you participate in or complete the application process and are denied, Mathematica may choose to terminate your employment.
We take pride in our employees and in their commitment to excellence. We encourage staff to collaborate in developing creative solutions to difficult problems and to share the responsibility and enjoyment of carrying out complex projects. This collegial spirit has helped us earn our reputation for innovative and high-quality work.