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Truveta · 1 day ago

Senior Applied Research Scientist – Oncology

Greater Seattle Area

Full-time

Hybrid

Senior Level

$158K/yr - $175K/yr

5+ years exp

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. They are seeking a motivated and innovative Applied Research Scientist with expertise in oncology to collaborate on high-quality research that transforms complex healthcare data into impactful insights. The role involves managing applied research studies, working with extensive datasets, and collaborating with various stakeholders to improve patient outcomes.

AnalyticsData ManagementHealth Care

No H1B

Responsibilities

Proactively initiate and drive applied research studies focused on oncology, from ideation through peer-review publication

Apply appropriate and rigorous methods for observational data studies, such as causal inference methods, missing data approaches, survival analysis, longitudinal data analysis, and time series analysis

Write, review, and maintain code (R or Python) to process, wrangle, and analyze data, identifying problems, devising solutions, and creating methodologies that drive data insights and best practices

Be accountable to agreed upon timelines for delivering research studies, working to communicate and manage dependencies

Proactively manage several projects simultaneously to maximize impact and efficiency of your work

Work collaboratively with internal and external stakeholders, including engineering, product, clinical informatics, and communications

Represent researcher input by providing feedback on the development of research solutions that enable clinicians and researchers to address real-world healthcare challenges

Qualification

Statistical ProgrammingApplied Methods ExpertiseScientific PublicationCross-functional CollaborationEHR Data ModelsLearn QuicklyTeam-OrientedPresentation SkillsCommunication Skills

Required

Education: MD or PhD in Epidemiology, HEOR, Biostatistics, or a related field

Expertise in Applied Methods: Extensive experience with statistical and econometric methods for analyzing complex real-world data, including approaches for causal inference, handling incomplete data, modeling longitudinal or time-to-event outcomes, and working with structured or hierarchical data

Statistical Programming: 5+ years of hands-on experience with statistical programming in R and/or Python, with experience executing analysis plans intended for publication, particularly within the health sciences

Scientific publication: 5+ years of experience developing research publications, including peer-reviewed manuscripts and conference abstracts, including handling peer review

Cross-functional Collaboration: 3+ years of experience partnering with cross-functional teams and effectively communicating research findings and needs to non-technical stakeholders

Team-Oriented and Results-Driven: Proven ability to work within cross-functional teams to deliver research under tight deadlines

Presentation & Communication: Demonstrated ability to present complex research findings to both scientific and non-scientific audiences, adapting messaging and depth to the needs of clinicians, researchers, executives, media, and lay stakeholders

Preferred

Thought leadership: Experience writing and/or speaking on real-world evidence, epidemiology, biostatistics, or related areas

Communication for lay audiences: Experience translating research findings for lay audiences

Scientific communication: Experience presenting research to both scientific and non-scientific audiences, tailoring complexity and interpretation for diverse stakeholders

Familiarity with EHR data models or clinical terminology: Understanding of oncology-relevant EHR data models, staging systems, tumor markers, treatment classes, and clinical vocabularies (e.g., ICD-10, SNOMED, LOINC, RxNorm)

Ability to learn quickly: Demonstrated capacity to rapidly absorb new methods, tools, and domain knowledge in a fast-paced environment