Senior/Staff Machine Learning Data Scientist
Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Oct 22, 2025. Bayesian Health scores B on the Alion truth index.
Senior/Staff Machine Learning Data Scientist
In Brief
We’re an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.
TLDR: Independent end-to-end model development with ability to work cross-functionally with Clinical, Engineering, and Product to clarify and prioritize specifications and features for our life-saving AI models.
Who We Are
Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.
We’re funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.
What you’ll do
As a Senior/Staff Machine Learning Data Scientist, you are not satisfied with training and tuning ML models that predict clinical conditions in patients; you also want to own the effectiveness of your model in the real world. In practice, that means you aren’t afraid to get your hands dirty by writing data mapping code, debugging a specific patient case by following patient data as it moves through our AWS services, or improving the timeliness of your model’s predictions by reading and writing production-grade Python and SQL code.
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
Minimum qualifications
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
Preferred 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 any of the following: PyTorch, PySpark, HL7, FHIR, EHR, time series data, signal processing, MLFlow, anomaly detection, Bayesian statistics, quantile regression, time-series forecasting
You bring passion and enthusiasm to your work, and are excited to join a growing team to Get Stuff Done and save lives!
Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.