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Senior Data Scientist

$180k - $260k
Full-time

Atria Health and Research Institute

Role Description

As a Senior Data Scientist at Atria, you will generate the medical insights and forecasts that shape how our clinicians care for members and how Atria runs as a practice. You'll work with one of the most distinctive longitudinal datasets in medicine: deep per-member baselines (whole-genome sequencing, advanced imaging, comprehensive labs, movement analysis, lifestyle inputs) revisited on cadence over years and linked across full family lineages, alongside the operational data of how a multi-disciplinary care team actually delivers that care. Your work spans both sides of that equation: surfacing clinically meaningful patterns clinicians can act on, and building the analyses, forecasts, and operational models that help Atria deliver better care more efficiently.

What you'll do

  • Generate medical insights from Atria's longitudinal clinical data: surface early signals of disease, characterize how members respond to interventions, and identify population-level trends clinicians can act on.
  • Build forecasting models on clinical and operational signals: disease progression, biomarker trajectories, member engagement, demand and capacity planning, and other time-series problems.
  • Lead or contribute to operational analytics: visit patterns, throughput and scheduling, panel composition, vendor performance, member journeys, and the quiet efficiency questions that compound over a year.
  • Design and execute studies in partnership with clinicians: clear questions, well-controlled comparisons, honest error analysis, and writeups that hold up to clinical scrutiny.
  • Design and analyze experiments (A/B tests, staged rollouts, quasi-experiments) with appropriate attention to power, multiple comparisons, and the difference between "statistically significant" and "actually mattered".
  • Author and maintain curated views and dbt models in our Snowflake gold layer, documented well enough that clinicians and operational staff can use them confidently without a Slack DM to you every Tuesday.
  • Build dashboards and analytical tools in Omni Analytics that clinicians and operational leaders actually use to make decisions.
  • Partner with the AI Scientists and AI Engineers on the boundary where analytical work meets model training and production systems: contributing ground truth, evaluation datasets, and the clinical framing that keeps their models pointed at the right problem.
  • Translate clinical and operational questions into well-formed analytical problems, and translate results back into clear recommendations. The translation in both directions is most of the job.
  • A bias to deliver. You would rather have a clear answer to a real question in front of a clinician next week than a beautiful methodology that ships next quarter.
  • A scrappy streak. You can pick up an unfamiliar dataset, statistical method, or clinical concept on a Wednesday and have a credible first cut by Friday.
  • A serious drive to keep getting better. You read other people's analyses, papers, and code. You treat being wrong as cheap information rather than an event requiring counseling.

Qualifications

  • Experience in data science, analytics, or applied statistics: 5+ years, with at least 2 in healthcare, biomedical, or another regulated longitudinal-data domain.
  • Strong foundation in statistics and probability: you can defend a confidence interval, a regression specification, and a sensible forecasting baseline honestly.
  • Solid working knowledge of forecasting and time-series methods (classical and modern), regression modeling, and applied ML for tabular data (gradient boosting and related).
  • Familiarity with the design and analysis of experiments and quasi-experiments: enough to know when an A/B test is the right tool, when it isn't, and what to do about it.
  • Strong Python (pandas, scikit-learn, statsmodels, and at least one forecasting library) and SQL that you write without apologizing for.
  • Comfort with a cloud warehouse (Snowflake preferred) and modern data tooling such as dbt and a workflow orchestrator (Dagster, Airflow).
  • Track record of partnering with domain experts and turning their questions into defensible analytical work: clinicians, ops leaders, or comparable stakeholders.
  • Clear written and visual communication: tight executive summaries, defensible methods sections, and charts that have titles, axes, and a point.
  • Interest in healthcare and the responsibility that comes with working on data that affects patient care.

Nice to have

  • Graduate degree in a quantitative field (statistics, biostatistics, epidemiology, computer science, applied math, or a relevant clinical/biological science), or a strong track record of analytical work in lieu of formal credentials.
  • Experience with causal inference methods.
  • Experience with modern forecasting toolkits and hierarchical or probabilistic forecasting.
  • Familiarity with modern deep learning tools (PyTorch, Hugging Face ecosystem): enough to collaborate productively with AI Scientists and Engineers.
  • Familiarity with a BI tool (Omni, Looker, Mode, Tableau).
  • Published peer-reviewed clinical, biomedical, or operations research.
  • Any prior work in healthcare, biology, or another regulated domain.

Salary

$180,000 - $260,000 Base Salary + performance-based bonus

Benefits

  • Excellent health and wellness benefits, fully covered by Atria, effective date of hire.
  • OneMedical membership for employees & dependents, giving access to 24/7 virtual care.
  • Fertility & family planning.
  • Company-covered preventive health screenings through partner hospitals (calcium score).
  • Fitness Perks, including Wellhub +.
  • 401k contributions and 4% match starting after 6 months.
Vacancy posted 21 hours ago
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