Full-Time

Senior Staff Machine Learning Data Scientist

Bayesian Health

Bayesian Health

11-50 employees

AI-powered clinical data insights platform

No salary listed

Remote in USA

Remote

Category
Data & Analytics (1)
Required Skills
Python
SQL
Machine Learning
Requirements
  • Ph.D. in a relevant field plus 3+ years experience shipping ML based software products
  • Experience owning your ML models from prototyping to production, especially real-time algorithms that update dynamically across time
  • Experience writing production-grade Python and SQL code to implement and evaluate ML models in production systems
  • Track record of using statistics and performance metrics to compare end-to-end ML and product performance
Responsibilities
  • Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods
  • Productionizing: The same models that you develop with production-grade Python
  • Deploying: Identify strategies for improving our production ML-based systems, and write, debug, and deploy production-grade Python code to implement those strategies
  • Cross-Functional Alignment: Data Science for storytelling – understand model performance and metrics, and present this to technical and non-technical users, both internally and externally
Desired Qualifications
  • Experience shipping breakthrough or 0-1 products from end to end, interpreting and leveraging State-of-the-Art methods to do so
  • Experience using messy clinical and health data to design new products for large Health Systems
  • Experience with PyTorch, PySpark, HL7, FHIR, EHR, time series data, signal processing, MLFlow, anomaly detection, Bayesian statistics, quantile regression, time-series forecasting
  • passion and enthusiasm to join a growing team to Get Stuff Done and save lives

Bayesian Health uses AI to help hospitals turn raw healthcare data into real-time, actionable insights for clinicians. Its platform continuously analyzes patient data and care workflows to support proactive, higher-quality care, especially for patient outcomes. How it works: a subscription-based platform that integrates with existing hospital systems, processes real-time data, and presents clinicians with actionable insights. It also provides ongoing updates, training, and customization to fit each provider’s needs. How it stands out: it combines rigorous scientific methods with practical AI tools, emphasizes real-time data analysis and proactive care, and offers strong integration and support typical for biotech-grade solutions. Its goal is to improve patient outcomes by enabling care teams to act on timely, data-driven insights inside hospitals.

Company Size

11-50

Company Stage

Late Stage VC

Total Funding

$30.2M

Headquarters

New York City, New York

Founded

N/A

Simplify Jobs

Simplify's Take

What believers are saying

  • Positioned for CMS NTAP reimbursement starting October 2026, enabling hospital incremental payments.
  • Partnerships with Cleveland Clinic and University of Rochester Medicine drive platform deployment.
  • William Porter, ex-Butterfly Network VP, appointed CCO to accelerate hospital sales expansion.

What critics are saying

  • Philips Healthcare and GE Healthcare gain FDA clearance for sepsis AI within 12 months, commoditizing market.
  • CMS denies NTAP by October 2026, forcing competition on subscriptions against cheaper rivals.
  • Post-market data shows only 5-10% mortality reduction, triggering hospital contract renegotiations in 2027.

What makes Bayesian Health unique

  • Bayesian Health secured first FDA 510(k) clearance for continuous AI sepsis monitoring on May 12, 2026.
  • Platform uses multi-model routing layer tuned to each patient's baseline, unlike one-size-fits-all scores.
  • Nature Medicine July 2022 studies show 18.2% mortality reduction across 764,707 encounters in five hospitals.

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Company News

Axios
Jun 3rd, 2023
Health Tech: 📇 Monthly movers

William Porter, former Butterfly Network VP, was named chief commercial officer of Bayesian Health.