About the role
Software Engineer, Analytics 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. You will lead the development of our clinical AI/ML product analytics infrastructure, frameworks, and tools to enable our client success, product, clinical, and technology teams to uplevel our decision making through better insights.
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: 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, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved.
What you'll do As a Senior Software Engineer, Analytics, you will work closely with client success, product managers, clinicians, data scientists, and other software engineers to build infrastructure, frameworks, and tools to improve client analytics, facilitate clinical case reviews, and support product investigation. This role is crucial to provide internal visibility into product performance that will drive expansion of our clinical AI/ML module offerings and revenue growth.
Responsibilities Product performance monitoring and optimization: Partner with client success and clinical product subject matter experts to implement the infrastructure, queries, and automation to monitor the KPIs and success metrics of our products across multiple clinical domains and clients. Clinical case review and investigation : Build frameworks and tools to empower our clinical team to independently review and investigate clinical cases reported by our clients and identify cases with certain criteria that need further evaluation. Data platform and analytics technical foundations: Propose and implement foundational improvements and innovations to boost our data platform scalability with expanding products and clients and uplevel our team analytics capabilities. Drive product analytics development cross-functionally: Work closely with Client Success, Clinical, Product, Data Science, and Engineering to drive alignment on product analytics at the company level. Minimum