Navvis (healthcare) · 13 hours ago
Data Scientist
United States
Full-time
Remote
Mid Level
3+ years expNavvis is a leading population health company focused on value-based care. The Data Scientist role involves designing rigorous program evaluations using healthcare data, developing analytic frameworks, and integrating machine learning algorithms to enhance healthcare outcomes.
Health CareMedicalmHealth
Responsibilities
Design and implement rigorous program evaluation studies using observational healthcare data
Develop analytic frameworks to measure outcomes such as cost reduction, quality improvement, and patient engagement
Apply causal inference methods, including PSM, DiD, IPTW, RDD, and other quasiexperimental approaches
Develop and validate statistical models to estimate treatment effects and assess program impact
Integrate machine learning algorithms (e.g., random forests, gradient boosting, neural networks) into predictive models using claims, EHR, SDOH, and clinical registry data
Work with structured and unstructured healthcare data to engineer features from demographics, clinical history, utilization patterns, costs, and SDOH
Build and refine predictive models for risk stratification and disease progression using longitudinal and time-to-event analysis
Collaborate with clinical, operational, and data engineering teams to embed models into workflows and develop scalable, reproducible data pipelines
Maintain transparent, governed, reproducible analytic workflows, including version controlled code and documentation
Contribute to best practices and methodological standards for program evaluation across the organization
Stay current with advancements in causal inference, ML, and healthcare analytics to strengthen evaluation rigor
Running causal inference analyses (e.g., matching, weighting, DiD) and performing sensitivity checks like parallel trends, placebo tests, and falsification strategies
Exploring and preparing healthcare datasets (claims, EHR, SDOH) and engineering features for modeling and evaluation
Estimating heterogeneous treatment effects to identify patient subgroups most likely to benefit from interventions
Developing predictive models for risk stratification, hospitalization risk, or high-cost event prediction
Reviewing model performance, refining assumptions, and troubleshooting data or methodological issues
Collaborating with clinicians, operational leads, or care-management partners to interpret findings and translate them into actionable insights
Creating visual analyses, dashboards, or presentations to communicate findings to both technical and non-technical audiences
Collaborate with data engineers to create scalable, reproducible, and high-quality data pipelines supporting evaluation and outcomes measurement
Documenting analytic decisions, version-controlling code, and completing peer reviews of methodological work
Qualification
Required
Master's or Ph.D. in Statistics, Biostatistics, Epidemiology, Health Economics, Data Science, or a related field
3+ years of experience in healthcare analytics, program evaluation, or applied statistics
Proficiency in statistical programming languages such as R or Python
Experience with healthcare data (claims, EMR, registry data, etc.) and high familiarity with data privacy regulations (e.g., HIPAA)
Strong understanding of causal inference methods and their application to real-world data
Experience with predictive modeling for risk stratification and disease progression in healthcare settings
Experience with VBC analytics, risk adjustment, health equity measurement, and population health management
Excellent communication skills and ability to translate complex analyses, assumptions, and study limitations into actionable insights for technical and non-technical audiences
Experience and passion for AI and automation
Preferred
Experience with heterogeneous treatment effect estimation (causal forests, meta-learners, uplift modeling)
Knowledge of sensitivity testing frameworks (robustness checks, placebo/falsification tests, parallel trends verification)
Familiarity with longitudinal or panel data modeling (fixed effects, random effects, mixed models)
Familiarity with machine learning frameworks and longitudinal/panel data modeling for disease trajectory analysis
Advanced data visualization skills (Tableau, Power BI)
Understanding of healthcare quality measures, risk adjustment, and population health management frameworks
Demonstrated ability to influence program or policy decisions through data-driven insights and impact measurement
Benefits
Medical
Dental
Vision
401K with a safe harbor contribution
Paid Time Off plan starting at 2+ weeks
Company
Navvis (healthcare)
Navvis is a leading value-based care enablement company, driving clinical, financial, and operational performance for healthcare organizations.
201-500 employees
H1B Sponsorship
Navvis (healthcare) has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (5)
2024 (6)
2023 (6)
2022 (5)
2021 (2)
Funding
Current Stage
Growth StageTotal Funding
$104.9M2022-10-20Acquired
2021-12-02Series Unknown· $80M
2020-11-18Series Unknown· $10M
Leadership Team
Courtney Fortner
President and CEO
Stuart Baker, MD
Chief Physician Executive, President Emeritus, Co-Founder, Board Director
Recent News
2025-11-29
Company data provided by crunchbase