About Bayesian Health
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, including Obvious Ventures, 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, and BioTech AI Company of the Year.
Role Overview
We’re looking for a software engineer to join the team to build and scale our data and analytical platform that tells us and our clients how our clinical AI products are performing in every hospital we serve. You’ll play an important role in shaping key technical decisions, building the data infrastructure our company and clients rely on, and see your work make a real difference in patient care.
You’ll work closely with other engineers, data scientists, clinicians, product managers, and client success partners to turn complex clinical data into reliable, actionable insights. Day to day, that means designing pipelines and data models, building tools that help our teams monitor product performance and investigate clinical cases, and improving the platform as we expand to new products and health systems.
Key Responsibilities
- Build the platform's foundations: Develop our data lakehouse and warehouse with secure, scalable pipelines that bring our data together to power analytics and machine learning. Drive improvements in data modeling, orchestration, data quality, and scalability as our products and client base grow.
- Enable self-serve insights with LLMs and automation: Create tools and frameworks that let Clinical, Client Success, and Product teams get answers from data without writing queries—from reviewing and flagging clinical cases to uncovering trends and opportunities.
- Power performance monitoring for clinical AI: Design pipelines and data models that automatically track KPIs and model performance across every client and clinical module using real-time EHR data that is messy and heterogeneous.
- Set the standard for analytics company-wide: Work across functions to define product success metrics and ensure underlying data is trustworthy.
Minimum Qualifications
- BS in Computer Science or relevant technical discipline.
- 5+ years of experience building scalable, secure data or analytics infrastructure on a cloud platform (preferably AWS) serving live products and customers.
- Proficiency in Python and SQL.
- Deep knowledge of modern data and analytics technologies (cloud data warehouses, transformation frameworks like dbt, workflow orchestration tools, BI tools like Tableau or QuickSight) and integrating them with existing infrastructure.
- Experience leveraging LLMs in distributed data processing and analytics systems.
- Excellent communication skills and proven ability to collaborate across data science, product, and clinical teams.
Preferred Qualifications
- Experience handling sensitive data containing PHI/PII securely.
- Experience building analytics technology for clinical or health data.
- Experience handling ambiguity and uncertainty in a startup environment.
Timezone overlap
UTC-8–-4
Benefits
Open to
US
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