Real World Data Analyst

Truveta•Seattle, WA

2d•$94,000 - $145,000•Hybrid

About The Position

Real World Data Analyst 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 . Truveta was born in the Pacific Northwest, but we have employees who live across the country. Our team enjoys the flexibility of a hybrid model and working from anywhere. In person attendance is required at least once per year for an onsite meeting. For overall team productivity, we optimize meeting hours in the pacific time zone. We avoid scheduling recurring meetings that start after 3pm PT, however, ad hoc meetings occur between 8am-6pm Pacific time. #LI-remote 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 The Real World Data Analyst role is a high-impact, intellectually challenging position that requires a diverse set of analytical and technical skills. It offers a unique opportunity for professional growth through access to an unprecedented volume of high-quality, real-world Electronic Health Record (EHR) data. In this role, you will tackle meaningful healthcare challenges using an EHR database encompassing more than 125 million patients—and growing—helping drive insights that can ultimately improve patient care. This position reports to the Senior Director of Research Services. As a Real World Data Analyst, you will collaborate strategically with some of our largest life sciences partners. This role provides the opportunity to dive deeply into complex research questions related to human health and generate data-driven insights that support impactful scientific decisions.

Requirements

Undergraduate or graduate degree in biostatistics, epidemiology, clinical research, data science, clinical informatics, or a related field.
3+ years of experience conducting analyses using large healthcare datasets (e.g., electronic health records or other real-world data sources).
Strong proficiency in SQL and at least one statistical programming language (R or Python) for data wrangling, analysis, and reproducible research workflows.
Experience translating research protocols or statistical analysis plans into executable analytical code.
Experience performing rigorous quality control of analytical datasets, code, and statistical outputs.
Demonstrated experience working with complex healthcare data involving millions of patient records.
Experience collaborating with research teams or customers to deliver high-quality scientific analyses.
Strong problem-solving skills and the ability to identify data or methodological issues early and communicate them effectively.
Excellent written and verbal communication skills, including the ability to clearly explain analytical approaches and findings to technical and non-technical stakeholders.
Ability to learn quickly and adapt in a dynamic, fast-paced environment.
Willingness to learn new analytical tools, programming languages, and proprietary platforms used to analyze real-world data.

Nice To Haves

Experience applying causal inference methods to observational healthcare data, including approaches such as propensity score matching/weighting, inverse probability weighting, marginal structural models, or instrumental variable analysis.
Familiarity with study designs used to estimate causal effects in real-world data, such as target trial emulation, difference-in-differences, regression discontinuity, or interrupted time series.
Experience evaluating confounding, selection bias, and other threats to causal validity in observational studies.

Responsibilities

Translate study protocols and statistical analysis plans (SAPs) into reproducible analytical code, executing end-to-end research studies from data extraction and wrangling through statistical analysis and results generation using SQL, R, or Python within agreed timelines.
Review and interpret study protocols and SAPs, ensuring analytical approaches are implemented accurately and consistently with study objectives.
Develop robust data pipelines for cohort building, data cleaning, feature engineering, and preparation of analytical datasets using large-scale real-world data sources.
Conduct rigorous quality control (QC) of code, datasets, and statistical outputs, including verification of model assumptions, reproducibility of results, and validation of analytical approaches.
Proactively identify and communicate potential data issues, methodological concerns, or deviations from study protocols early in the research process, recommending solutions and mitigation strategies.
Collaborate closely with biostatisticians and researchers to support the development, refinement, and review of statistical analysis plans and analytical methods.
Interpret analytical results and contribute to the synthesis of findings, ensuring outputs are scientifically sound and aligned with study objectives.
Partner with life sciences customers and internal teams to execute high-quality analyses that support peer-reviewed publications, regulatory submissions, and scientific research.
Provide clear, proactive communication on study progress, analytical challenges, and timelines, ensuring stakeholders remain informed and aligned.
Work closely with cross-functional teams across Truveta to investigate data sources, validate data integrity, and support scientific credibility of research outputs.
Deliver feedback to internal teams based on research experiences and customer needs to help inform improvements to Truveta’s data platform and research capabilities.