Data Analytics - SQL, SAS, Python, Databricks - Bachelor's Intern

FLEXIBLE: This internship role is scheduled to be flexible. Please be prepared to spend part of your time working remotely and part of your time working at the following address: 199 S. Los Robles Ave., Pasadena, 91101.

Under supervision assists in the provision of information, maintenance of databases, report production and routine data analysis. Work is reviewed for completeness, accuracy and soundness.

Department Description:

SCPMG Clinical Analysis empowers informed decision-making through data insights and analyses for regional and national audiences. Our department provides a wide range of clinical data analyses and regulatory reporting, program evaluations across clinical conditions and specialties, medical device surveillance and analyses, evidence-based medicine services, cancer registry, and Clarity database research and user support. We are dedicated to delivering accurate, timely, and actionable information that drives excellence in health outcomes, equity, and operational efficiency across Southern California and throughout the Kaiser Permanente regions.

Project Description:

The Intern will support the Clinical Analysis department-s SAS-to-Python migration on the Databricks platform. The work will include helping inventory and assess existing SAS programs, translating SAS logic into Python/SQL/PySpark within Databricks notebooks, and validating that new workflows produce results consistent with legacy outputs. You-ll build and test modular notebooks, apply enterprise naming and data-governance standards, document reusable patterns, and assist with integrating migrated datasets into downstream tools such as Power BI. You will also participate in Databricks onboarding, training, and migration working sessions, contributing insights and updates to the broader transition effort.

Sample Deliverables: Migrated SAS workflows rewritten in Python/SQL within Databricks notebooks, with validated output parity
Documentation of migration steps, coding patterns, and recommendations for scaling future conversions
A small reusable library or template (e.g., starter notebook, helper functions, or testing checklist) to support analyst teams
A brief summary of findings, challenges, and lessons learned from the migration work.

Desired Skillsets:

Basic proficiency in Python (e.g., writing simple scripts, working with dataframes, or completing introductory coursework)
Foundational knowledge of SQL, including selecting, filtering, and joining tables
Ability to analyze and understand existing code or logic, even if written in unfamiliar languages (e.g., SAS)
Strong analytical and problem-solving skills with attention to detail
Ability to document processes, findings, and results clearly
Willingness to learn new tools and platforms, including Databricks, GitHub, and Power BI
Effective verbal and written communication skills
Ability to work collaboratively in a fast-paced, project-driven environment
Commitment to handling sensitive healthcare data responsibly and following data governance guidelines.

Desired Majors:

Computer Science, Math/Statistics, Data Science, Healthcare Administration, Business Administration, Public Health.

Examples of project support include: Collects, prepares and tracks reports and summaries such as: budget to actual expenditures, production statistics, and utilization of services and statistical records of performance. Performs a variety of data collection and analysis assignments. Prepares ad hoc data requests as directed. Prepares and/or formats graphs, spreadsheets and reports by utilizing office software. May be asked to maintain databases on a regular basis by entering data and preparing data extracts. May extract information from different sources to compile data. Executes existing queries for established reports.  Schedules conference calls and meetings. Contributes to the development of presentations materials. Provides administrative and project support as assigned such as copying, filing, entering and extracting data. Engages in and supports project work.  Kaiser Permanente conducts compensation reviews of positions on a routine basis. At any time, Kaiser Permanente reserves the right to re-evaluate and change job descriptions, or to change such positions from salaried to hourly pay status. Such changes are generally implemented only after notice is given to affected employees.