Software Engineer, Analytics
Builds analytics infrastructure, frameworks, and tools for monitoring clinical AI/ML product performance, enabling clinical case reviews, and driving cross-functional insights. Requires 5+ years experience with Python, SQL, cloud data platforms, and handling sensitive health data.
About the job
Responsibilities
- 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 products across multiple clinical domains and clients.
- Build frameworks and tools to empower the clinical team to independently review and investigate clinical cases reported by clients and identify cases with certain criteria that need further evaluation.
- Propose and implement foundational improvements and innovations to boost data platform scalability with expanding products and clients and uplevel team analytics capabilities.
- 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.
Skills
Python, SQL, AWS, dbt, Tableau, Amazon Quicksight, Data Warehouses, Workflow Orchestration, LLMs
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