Machine Learning Researcher

We seek to fill a part-time temporary position (14 hours/week) for a Causal Machine Learning Researcher to design and implement machine learning analyses of the results of evaluations of social and economic programs. The role combines modern machine learning with applied econometrics to estimate program impacts and produce evidence that supports real-world decision making.

Responsibilities:

• Build and maintain end-to-end analysis pipelines in Python for causal and predictive modeling using large, micro-level datasets
• Apply modern causal ML methods (such as Double ML, BLP, GATES, CLAN) to estimate treatment effects and related quantities of interest
• Use cross-fitting, resampling, and multiple model specifications to check the robustness and stability of results
• Prepare clear documentation, code, and research outputs that make analyses reproducible and suitable for internal use and potential publication
• Communicate key findings and methodological choices in a clear, concise way to both technical and non-technical collaborators.
  
  

Minimum Qualifications:

• Bachelor's degree
• Graduate-level coursework in econometrics, statistics, data science, and economics
• Strong programming skills in Python, including experience with libraries such as pandas, NumPy, scikit-learn, and tree/boosting methods
• Solid understanding of causal inference concepts, including treatment effects, identification strategies, and common sources of bias
• Experience applying modern machine learning methods in combination with econometric tools to answer real research or policy questions
• Prior involvement in at least one substantial, applied research project aimed at informing institutional or policy decisions.

Preferred Qualifications:

• Ability to translate complex analysis into clear, actionable insights through written reports and visualizations
• Hands-on experience with causal inference methods beyond standard regression (for example, propensity score approaches, double/debiased ML, or related techniques)
• Proven experience designing and implementing causal machine learning pipelines for program or policy evaluation.

Pay Range: $27-28 per hour; depending on education/qualifications/experience.

Retirement plan options are available for Civil Service, Faculty, Labor-Represented, Professional & Administrative, and Temp Casual classifications. Learn more about retirement plans.

While our salary ranges provide a framework, it is important to note that most of the time, the initial pay may not reach the maximum of the range. This approach ensures that compensation reflects the value and unique contributions of each candidate while maintaining equity within our organization. As part of our commitment to fair and equitable compensation, please be aware that the salary offered to incoming candidates will be based on their individual credentials and experience.

Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online application for the position and attach a cover letter and resume.

Additional documents may be attached after application by accessing your "My Job Applications" page and uploading documents in the "My Cover Letters and Attachments" section.

To request an accommodation during the application process, please e-mail employ@umn.edu or call (612) 624-8647.

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.

The University of Minnesota, Twin Cities (UMTC)

The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

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