About this role.
Bayesian Health is seeking a senior software engineer to lead development of analytics infrastructure for a clinical AI/ML product. The role builds monitoring, investigation, and data-platform capabilities that help product, clinical, client success, and engineering teams understand product performance. Key technical work includes cloud-based data infrastructure, complex SQL and Python workflows, data warehousing, dbt, orchestration, and BI tooling. The engineer will work with sensitive PHI/PII and translate cross-functional clinical and product needs into scalable technical solutions. This is a remote, US-only position in an early-stage healthcare startup environment.
Role DNA
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Job Complexity
5/5Pace & Pressure
4/5Autonomy Level
5/5Communication Load
5/5Salary analysis
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Core skills
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Sample interview questions
I would begin by defining standardized KPIs, data contracts, ownership, and freshness expectations with clinical, product, and client-success partners. I would build an extensible warehouse model and transformation layer, add automated quality checks and lineage, then expose role-appropriate dashboards and alerts. I would also ensure tenant isolation, auditability, and PHI-minimizing access patterns from the start.
I apply least-privilege access, encryption in transit and at rest, strong audit logging, and clear data-retention controls. I prefer de-identified or limited datasets whenever they satisfy the analytic need, and I partner with security and compliance teams to document controls and validate access workflows. I also build tests that prevent sensitive fields from appearing in inappropriate downstream models or dashboards.
I use SQL to efficiently isolate relevant events and join operational datasets, then use Python for repeatable analysis, validation, anomaly detection, and report generation. I package common investigative logic into version-controlled tools or workflows so clinical and support partners can answer routine questions safely without engineering intervention. This shortens incident investigation while improving consistency.
I would first profile the workload across ingestion, transformations, storage, query patterns, and BI usage to identify the real bottlenecks. I would prioritize high-value improvements such as incremental models, partitioning, materialized aggregates, orchestration reliability, and data-quality observability. I would deliver changes in measurable increments, tracking cost, freshness, runtime, and user impact.
I turn ambiguity into a structured discovery process: clarify the decision to be made, define users and success metrics, identify available data and constraints, and propose a small, testable first version. I communicate tradeoffs in plain language and document assumptions so stakeholders can respond quickly. This keeps progress moving while ensuring the solution addresses a meaningful clinical or product question.
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.
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 qualifications
BS in Computer Science or other relevant technical discipline.
5+ years of experience in building scalable, secure analytics infrastructure and tools on a cloud platform (preferably AWS) to produce monitoring metrics and investigational data from complex data models and queries for live products and customers.
Proficient in Python and SQL.
Deep knowledge in modern data and analytics technologies, such as cloud-based data warehouses, transformation frameworks (e.g. dbt), workflow orchestration tools, and BI tools like Tableau or Quicksight, and keen ability to integrate with existing infrastructure to enhance capabilities.
Experience working with sensitive data that contains PHI/PII.
Excellent communication skills and a proven ability to collaborate with cross-functional teams (data science, product, clinical) to translate requirements into robust technical solutions
Preferred qualifications
Experience in leveraging LLMs in distributed data processing and analytics systems.
Experience building analytics technology for clinical/health data.
Experience handling ambiguity and uncertainty in a startup.
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.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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