Data Scientist 1

Data Scientist 1

Requisition ID
req35174

Working Title
Data Scientist 1

Position Grade
14

Position Summary

UNM Center for Teaching and Learning is looking for a talented individual to join our team and serve in the position of Data Scientist I. The person selected for this position will report to the Director for the Office of Institutional Analytics, with a dotted line to the CTL Executive Director. This position also works closely with leaders of Student Learning Assistance and Graduate Support as well as Teaching Support and Digital Learning. They will provide a wide array of data organization, processing, analysis, and reporting for CTL and partner units that rely on CTL data. This position will apply advanced analytical, statistical, and visualization techniques to examine student learning outcomes, instructional practices, and institutional performance indicators. The Data Scientist will operationalize predictive and diagnostic models, design and manage data pipelines, and translate complex analyses into actionable insights that inform policy, pedagogy, and program design.

See the Position Description for additional information.

Conditions of Employment

• Employees who provide services or work in patient care or clinical areas are required to be in compliance with the University's influenza vaccination requirement.

Minimum Qualifications

Bachelor's degree in a relevant field; at least 3 years of experience directly related to the duties and responsibilities specified.

Completed degree(s) from an accredited institution that are above the minimum education requirement may be substituted for experience on a year for year basis.

Preferred Qualifications

The ideal candidate will be self-directed with excellent verbal and written communication skills as well as strong data analysis, management, and organization competence. They will have demonstrated capabilities in the following areas:

• ·       Experience creating, cleaning, and analyzing large data sets and sensitive data. 
• ·       Knowledge of FERPA and application to educational data
• ·       Experience with statistical programs such as Excel, SPSS, R, and/or other software. 
• ·       Experience using R, Python, or similar approaches to cleaning data. 
• ·       Experience conducting statistical analyses and hypothesis testing (e.g., regression, multiple regression, contingency analyses, ANOVA, MANOVA, t-tests, A/B testing, etc.).
• ·       Experience creating, documenting, and training others on data workflows. 
• ·       Experience designing and maintaining dynamic dashboards and visualizations (e.g., Tableau, Power BI, or similar platforms) that communicate complex information to faculty, staff, and administrators.
• ·       Analytical skills such as quantitative analysis, root cause analysis, and pattern recognition
• ·       Experience with data storytelling via reports, presentations, figures and campus partnership communication
• ·       Knowledge of common data needs and collection in higher education (e.g., predictors of student retention and/or graduation rates, demographic covariates)
• ·       Experience conducting quantitative and qualitative analyses—such as regression, hypothesis testing, and longitudinal modeling—to evaluate teaching, tutoring, and instructional interventions.
• ·       Experience developing, testing, and refining statistical and machine learning models to identify key drivers of student learning, retention, and academic success.
• ·       Supervising and mentoring staff and student employees involved in data collection, coding, and analysis.
• ·       Promotes data literacy, responsible data use, and equity-focused analytics

Additional Requirements

Campus
Main - Albuquerque, NM

Department
Provost Office Staff (688A)

Employment Type
Staff

Staff Type
Regular - Full-Time

Term End Date

Status
Exempt

Pay
Monthly: $4, $6,976.67

Benefits Eligible
This is a benefits eligible position. The University of New Mexico provides a comprehensive package of benefits including medical, dental, vision, and life insurance. In addition, UNM offers educational benefits through the tuition remission and dependent education programs. See the Benefits home page for a more information.

ERB Statement
As a condition of employment, eligible employees working greater than .25 FTE as determined by the New Mexico Education Retirement Act must make mandatory retirement contributions. For more information, review the Benefits Eligibility at a Glance grid.

Background Check Required
Yes

For Best Consideration Date
12/1/2025

Eligible for Remote Work
Yes

Eligible for Remote Work Statement
After the first 30 days of employment, the new employee may be eligible for a hybrid remote work (telecommuting) arrangement under the discretion of their supervisor, business needs, and successful completion of training.

Application Instructions

Only applications submitted through
the official UNMJobs site will be accepted. If you are viewing this job
advertisement on a 3rd party site, please
visit UNMJobs to submit an application.

Interested candidates should submit a resume and cover letter for consideration. The cover letter should address your experience and career goals as a Data Scientist/Supervisor in the university setting. Your application will not be considered without a cover letter.

Positions posted with a Staff Type of Regular or Term are eligible for the Veteran Preference Program. See the Veteran Preference Program webpage for additional details.

The University of New Mexico is committed to hiring and retaining a diverse workforce. We are an Equal Opportunity Employer, making decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability, or any other protected class.

The University of New Mexico requires all regular staff positions successfully pass a pre-employment background check. This may include, but is not limited to, a criminal history background check, New Mexico Department of Health fingerprint screening, New Mexico Children, Youth, and Families Department fingerprint screening, verification of education credentials, and/or verification of prior employment. For more information about background checks, visit Refer to for a definition of Regular Staff.

---