Learning Analytics Data Scientist

APPLICATION INSTRUCTIONS:

• CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.
• CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.
• If you are NOT a current employee or student, please click "Apply" and complete the application process for external applicants.

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional information on remote work at Penn State, seeNotice to Out of State Applicants.

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POSITION SPECIFICS​

Penn State IT invites a Learning Analytics Data Scientist to join the award-winning Data Empowered Learning team. In this role, you will assist in the creation of the models and insights that power cutting-edge tools like Course Insights and Elevate. You will join a mission-driven, collaborative team dedicated to delivering insights that enhance student success and institutional efficiency across Penn State. We are looking for a candidate with proven expertise across the entire data science lifecycle, from organizing complex institutional datasets to applying advanced analytical and modeling methods.

Key Responsibilities

• Design, validate, and deploy predictive and descriptive models (e.g., student-at-risk indicators, and engagement patterns, etc) to inform institutional strategy.
• Architect and maintain complex data workflows by retrieving and organizing institutional data from diverse sources, including Canvas (LMS), Starfish, and Student Information Systems (SIS).
• Utilize exploratory data analysis and machine learning to transform raw data into high-level trends and actionable recommendations.
• Collaborate with university leadership to move insights from theory to practice, ensuring findings are translated into intuitive, practical tools for faculty and advisors.
• Communicate to technical and non-technical stakeholders and audiences on data and methodological questions.
• Partner with software developers to transition successful models into production-level applications used by thousands of users across the university.

QUALIFICATIONS

Required

• Extensive experience with the Python data stack (pandas, NumPy, etc.) for data cleaning, feature engineering, and high-level statistical modeling.
• A robust background in quantitative methods, including regression, clustering, decision trees, and experimental design.
• Expertise in writing complex SQL queries to extract and manipulate data within relational databases.
• Proven ability to synthesize technical findings into clear, compelling, non-technical narratives for executive-level stakeholders.
• Exceptional attention to detail and a commitment to the ethical use of data in the educational environment.
• Experience with managing production-level data and code through version control and continuous integration/continuous deployment (CI/CD) workflows, such as GitHub Actions, or similar automation tools to manage the model lifecycle

Desired

• Degree in Data Science, Computer Science, Information Science, or a related field.
• Experience inheriting existing production level codebases or comfortable jumping into new codebase to debug, refactor, make improvements, etc.
• Familiarity with R for supplementary statistical analysis or collaborative research scripts.
• Experience with data visualization libraries (e.g., Plotly, Matplotlib) to create impactful visual stories.
• Experience architecting and deploying RESTful APIs to serve machine learning models using frameworks such as FastAPI (Python) or Plumber (R).
• Understanding of the Higher Education ecosystem, including FERPA compliance and the nuances of SIS and LMS data structures.

MINIMUM EDUCATION, WORK EXPERIENCE & REQUIRED CERTIFICATIONS

acceptedRequiredCertifications:None

BACKGROUND CHECKS/CLEARANCES

SALARY & BENEFITS

Salary Structure - Information on Penn State's salary structure

Penn State provides a competitive benefits package for full-time employees designed to support both personal and professional well-being. In addition to comprehensive medical, dental, and vision coverage, employees enjoy robust retirement plans and substantial paid time off which includes holidays, vacation and sick time. One of the standout benefits is the generous 75% tuition discount, available to employees as well as eligible spouses and children. For more detailed information, please visit our Benefits Page.

CAMPUS SECURITY CRIME STATISTICS

Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters. The ASR is available for review here.

EEO IS THE LAW

Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814-865-1473.

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