Learning Analytics Data Scientist
About The Position
Penn State IT invites a Learning Analytics Data Scientist to join its Data Empowered Learning team. The role supports the creation of models and insights that power tools such as Course Insights and Elevate. The team works collaboratively to deliver insights that enhance student success and institutional efficiency across Penn State. The successful candidate will bring expertise across the data science lifecycle, from organizing complex institutional datasets to applying advanced analytical and modeling methods. The position involves developing and maintaining data workflows, building and deploying models, and translating findings into useful tools and recommendations for university stakeholders.
Requirements
- Extensive experience with the Python data stack, including pandas and NumPy, for data cleaning, feature engineering, and statistical modeling.
- Robust background in quantitative methods, including regression, clustering, decision trees, and experimental design.
- Expertise writing complex SQL queries to extract and manipulate data in relational databases.
- Ability to synthesize technical findings into clear, compelling narratives for non-technical, executive-level stakeholders.
- Exceptional attention to detail and commitment to ethical data use in education.
- Experience managing production-level data and code using version control and CI/CD workflows, such as GitHub Actions or similar tools.
- Master's degree.
- Six or more years of relevant experience, or an equivalent combination of education and experience.
- Applicants must be authorized to work in the U.S.; Penn State does not sponsor or take over sponsorship of a staff employment visa.
- Successful completion of background checks in accordance with University policies.
Nice To Haves
- Degree in Data Science, Computer Science, Information Science, or a related field.
- Experience inheriting production-level codebases or debugging, refactoring, and improving unfamiliar codebases.
- Familiarity with R for supplementary statistical analysis or collaborative research scripts.
- Experience with data visualization libraries such as Plotly or Matplotlib.
- Experience architecting and deploying RESTful APIs to serve machine learning models using FastAPI (Python) or Plumber (R).
- Understanding of higher education, including FERPA compliance and SIS and LMS data structures.
Responsibilities
- Design, validate, and deploy predictive and descriptive models, such as student-at-risk indicators and engagement patterns, to inform institutional strategy.
- Architect and maintain data workflows using institutional data from sources including Canvas, Starfish, and Student Information Systems (SIS).
- Use exploratory data analysis and machine learning to turn raw data into high-level trends and actionable recommendations.
- Collaborate with university leadership to translate insights into practical tools for faculty and advisors.
- Communicate about data and methodological questions with technical and non-technical stakeholders.
- Partner with software developers to transition successful models into production-level applications used across the university.
Benefits
- Comprehensive medical, dental, and vision coverage.
- Retirement plans.
- Paid holidays, vacation, and sick time.
- 75% tuition discount for employees and eligible spouses and children.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
