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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.
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Remote Causal Inference jobs near you
Post-doctoral Research Associate - Department of Educational Leadership and Policy Studies - UTK

Post-doctoral Research Associate - Department of Educational Leadership and Policy Studies - UTK

The University of Tennessee

Knoxville, TN • On-site, Remote

Full-time

Posted 19 days ago

Job description

This postdoctoral fellowship at the University of Tennessee, Knoxville (UTK) will join a pilot project exploring how AI can support high quality teaching and learning in research methodology courses. The scholar will investigate student and instructor perceptions of AI-assisted learning, evaluate pedagogical frameworks for effective design and implementation, and analyze both computational and qualitative data to refine AI integration in higher education. The position emphasizes building scalable, ethical, and culturally conscious approaches to AI in teaching, while contributing to faculty development and institutional capacity. Outcomes will include evidence-based practices, publications, and positioning UTK for major external funding and industry collaborations. This position will be working in the AIRELab. 

Required Qualifications

  • Education: PhD in Education, Computer Science, Learning Sciences, Economics, Psychology, Public Policy, or a related field.
  • Experience working across disciplines (education, tech, public policy, health, etc.) Strong training in quantitative methods (e.g., regression, causal inference, psychometrics, experimental & quasi-experimental designs)
  • Demonstrated experience with mixed-methods research (integrating qualitative + quantitative data

Applicants must be legally authorized to work in the United States on a full-time basis without need now or in the future for sponsorship for employment visa status.

Knowledge, Skills, Abilities:

  • Track record of peer-reviewed publications
  • Interest in equity-centered, applied research at the intersection of AI, education, and the labor market
  • Comfort translating research into scalable, real-world educational interventions
  • Experience with grant writing. 

Work Location 

  • Location: University of Tennessee, Knoxville, Tennessee, 37996
  • Onsite, Hybrid, or Remote: Onsite 

Compensation and Benefits 

  • Anticipated hiring range: 60K-70K
  • Find more information on UT Benefits here

Application Instructions 

To express interest, please submit an application with the noted below attachments. To be assured of full consideration, completed applications with all requested materials should be submitted. 

  • Resume
  • Cover Letter
  • List of 3 Professional References

  • Two writing samples (peer reviewed journal articles or working papers.

We will begin reviewing candidates after March 30th, and will continue reviewing until the position is filled.

About The College/Department/Division 

The Department of Educational Leadership and Policy Studies (ELPS) prepares administrators for schools and colleges, faculty for colleges and universities, and policy scholars for service in state, regional and national agencies associated with educational and human service enterprises. The department is comprised of nineteen faculty and five staff. 

  • Lead and co-author quantitative and mixed-methods studies based on the main project.
  • Support experimental and pilot interventions in education and workforce training
  • Design and evaluate AI-integrated curricula and learning tools
  • Contribute to grant writing, IRB protocols, and peer-reviewed publications
  • Support curriculum design and implementation.
  • Facilitate professional development workshops for collaborators
  • Mentor graduate and undergraduate researchers in quantitative methods
  • Collaborate with domestic and international partners on program design and deployment
  • Support design of data dashboard

Apply