Applied Research Scientist - Life Science Partnerships

Truveta•Seattle, WA

17h•Hybrid

About The Position

This Applied Research Scientist, Strategic Partnerships position is a high-impact, customer-facing role that requires a diverse set of skills spanning technical execution, applied research methodology, and relationship management. You will work directly with life sciences partners to translate research questions into analytical approaches, execute studies using real-world Electronic Health Record (EHR) data (~120M+ patients), and guide customers in best practices for real-world evidence generation. You will play a key role in advancing customer research by helping shape analytical approaches, ensuring methodological rigor, and driving projects forward from question to insight. While customers may define or co-develop study protocols, you will provide guidance on study design, bias considerations, statistical approaches, and interpretation of results. This role requires balancing rapid-response analytical support with deeper, more complex investigations, while maintaining a high bar for scientific rigor and customer experience.

Requirements

Undergraduate or graduate degree in clinical research, epidemiology, biostatistics, data science, clinical informatics, or a related field
5+ years of experience working in a technical customer-facing role, delivering high-quality research studies & analyses.
3+ years of experience wrangling and analyzing Electronic Health Record data or other Real World Data sources in life science companies, CROs, other EHR data companies or healthcare organizations.
Strong proficiency in SQL, R and/or Python for statistical analysis
Experience working across large, multi-domain healthcare datasets with millions of patients and hundreds of millions of records, leveraging distributed computing frameworks for scalable analysis.
Willingness to learn new coding languages including internal proprietary coding language to analyze data and build cohorts.
Strong understanding of real-world evidence principles, including bias, confounding, and study design considerations.
Demonstrated experience applying research methodologies, including cohort design and statistical approaches.
Experience delivering high-quality product demonstrations that enable customers or stakeholders to understand and effectively leverage data, platform capabilities, and analytical workflows.
Proven ability to learn, adapt, and independently drive multiple projects forward in a fast-paced, start-up environment.
Strong executive presence with the ability to build credibility and trust across stakeholders and effectively communicate complex technical concepts to both executive and technical audiences.

Nice To Haves

Advanced degree (MS, MPH, PhD) in epidemiology, biostatistics, health economics, or related field
Experience supporting or contributing to peer-reviewed publications or conference abstracts
Knowledge of advanced statistical methods such as regression, propensity score methods, survival analysis, and longitudinal data analysis
Experience applying methods for causal inference or handling incomplete data in observational research
Experience with Spark/PySpark or distributed data processing
Experience with Regression, Propensity Score Matching, Kaplan-Meier Analyses, or Survival Analyses
Experience working in customer-facing or consulting-style roles
Demonstrated ability to present research findings to both technical and non-technical audiences

Responsibilities

Partner closely with life sciences customers to understand research questions and translate them into analytical approaches
Required to excel in providing technical analytics support as well as directly working with customers on calls to troubleshooting customer analysis.
Use technical skills to scope out customer analyses requests, produce studies and results using SQL, R and Python within an agreed upon deadline.
Build strong, trusted relationships with customer stakeholders, acting as a key partner in advancing their research goals
Apply appropriate research methodologies, including cohort design, bias mitigation, and statistical analysis
Communicate on the status of various projects and collaborate with success managers to ensure that Truveta clients can be successful with the platform.
Guide customers on best practices in real-world data research, including study design tradeoffs and interpretation of results
Lead customer-facing discussions to unblock research challenges and drive projects forward
Collaborate with customers to support peer-reviewed publications and high-quality research outputs
Deliver both rapid-response analyses and deeper, in-depth investigations depending on customer needs
Provide technical support and troubleshooting for customer analyses, code, and notebooks
Create enablement materials as the Truveta platform evolves to help onboard new researchers to our increasing capabilities.
Collaborate cross-functionally to investigate data quality and demonstrate data reliability
Deliver feedback to internal teams based on customer requests to inform Truveta’s product roadmap.