Software Engineer, Data & Analytics Platform

Bayesian Health, Inc.

5h

About The Position

Bayesian Health is seeking a software engineer to build and scale the data and analytics platform used to evaluate how its clinical AI products perform across hospitals. The role involves shaping technical decisions and developing the data infrastructure that the company and its clients rely on to understand product performance and support patient care.

The engineer will work closely with engineers, data scientists, clinicians, product managers, and client success partners to turn complex clinical data into reliable, actionable insights. This includes designing pipelines and data models, building tools for monitoring product performance and investigating clinical cases, and improving the platform as the company expands to additional products and health systems.

Requirements

• Bachelor of Science in Computer Science or another relevant technical discipline.
• At least 5 years of experience building scalable, secure data or analytics infrastructure on a cloud platform, preferably AWS, for live products and customers.
• Proficiency in Python and SQL.
• Deep knowledge of modern data and analytics technologies, such as cloud-based data warehouses, transformation frameworks such as dbt, workflow orchestration tools, and BI tools such as Tableau or Quicksight.
• Ability to integrate modern data and analytics technologies with existing infrastructure to enhance its capabilities.
• Experience leveraging LLMs in distributed data processing and analytics systems.
• Excellent communication skills and a proven ability to collaborate with cross-functional teams, including data science, product, and clinical teams, to translate requirements into robust technical solutions.

Nice To Haves

• 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.

Responsibilities

• Develop the data lakehouse and warehouse, including secure, scalable pipelines that bring data together for analytics and machine learning.
• Improve data modeling, orchestration, data quality, and scalability as products and the client base grow.
• Create tools and frameworks that enable Clinical, Client Success, and Product teams to get answers from data without writing queries, including reviewing and flagging clinical cases and identifying trends and opportunities.
• Design pipelines and data models that automatically track KPIs and clinical AI model performance across clients and supported clinical modules, using real-time EHR data.
• Collaborate with Client Success, Clinical, Product, Data Science, and Engineering teams to define measures of product success and ensure the underlying data is trustworthy.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level