Research Analyst Summer Intern

Truveta•Seattle, WA

17h•Hybrid

About The Position

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values. This role will be based in the Greater Seattle area and interns are asked to come into our office several days per week. #LI-hybrid Who We Need Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you. This Opportunity We are seeking a Research Analyst Intern to join our team and support the generation of real-world evidence using Truveta’s data platform. This role offers a unique opportunity to gain hands-on experience with large-scale electronic health record (EHR) data and contribute to research that validates and demonstrates the power of Truveta’s dataset across multiple clinical domains. In this role, you will learn how to effectively use the Truveta platform and apply it to reproduce published studies in areas such as cardiology and oncology. By scaling these studies across a significantly larger and more diverse dataset, you will help demonstrate alignment with real-world findings while showcasing the breadth and depth of Truveta data. You will also contribute to the development of reusable, “plug-and-play” study and manuscript templates that enable efficient and reproducible research workflows. The ideal candidate is intellectually curious, detail-oriented, and excited about translating data into meaningful scientific insights.

Requirements

Currently pursuing a Bachelor’s, Master’s, or Ph.D. in Epidemiology, Biostatistics, Data Science, Public Health, Health Informatics, or a related field.
Strong analytical and problem-solving skills with attention to detail.
Experience with data analysis using tools such as R, Python, SQL, or similar.
Basic understanding of observational study design and real-world data (RWD).
Strong written and verbal communication skills, with an interest in scientific writing.
Ability to work independently while collaborating effectively within a team environment.

Nice To Haves

Coursework or experience in epidemiology, biostatistics, or clinical research methods.
Familiarity with healthcare data, including EHR or claims data.
Exposure to medical terminologies such as ICD-10, CPT, LOINC, SNOMED, or RxNorm.
Experience reading and interpreting scientific literature and translating methods into reproducible analyses.
Interest in developing reusable research frameworks, templates, or tooling.

Responsibilities

Learn and apply the Truveta data model, research platform, and analytic tools to conduct observational research studies.
Reproduce published clinical studies across multiple therapeutic areas (e.g., cardiology, oncology) using Truveta data, ensuring methodological rigor and comparability.
Scale analyses to leverage the breadth of Truveta’s dataset, evaluating consistency of findings with existing literature and identifying opportunities for deeper insight.
Collaborate with team members to design study cohorts, define variables, and implement analytic approaches aligned with published methodologies.
Draft and contribute to scientific manuscripts, abstracts, and reports that clearly communicate study design, methods, and findings.
Develop reusable templates for both study execution within the Truveta platform and manuscript preparation to support efficient, repeatable research workflows.
Ensure high standards of data quality, reproducibility, and documentation throughout all stages of analysis.
Present findings to internal stakeholders and incorporate feedback to refine analyses and outputs.