Head of Data Product Quality
Posted on 2/23/2023
Komodo Health

501-1,000 employees

Healthcare intelligence & transparency software
Company Overview
Komodo’s mission is to reduce the global burden of disease through their actionable Healthcare Map platform that answers healthcare’s most complicated questions. The platform delivers patient-level insights by dynamically analyzing the broadest array of data across patients, practitioners, and health systems.
San Francisco, CA, USA • Chicago, IL, USA • New York, NY, USA
Experience Level
Desired Skills
Apache Spark
DevOps & Infrastructure
  • Healthcare Customer Understanding - Deep knowledge of what our customers (Life Sciences, Payers, Providers) do with data products, the insights they need, and how they use them
  • Healthcare Data Knowledge - Deep knowledge on Claims and EHR data (e.g. CMS-1500/UB-04, EDI); Knowledge of the US healthcare landscape
  • Hands-on Expertise and Implementation - Experience with Python scripting and automation, SQL data querying, Fluency with or similar to modern platform tools and technologies such as Snowflake, Databricks, Alteryx, cloud computing, AWS, Spark, SQL, Apache Airflow, etc
  • Clear communications - Effective oral and written communication skills with the purpose of bringing clarity to complexity and communicating to inform and influence across cross-functional teams and leadership
  • Experience leading quality improvement efforts related specifically to data products, preferably in the life sciences or healthcare space
  • Gathered customer perspectives on how they defined quality and synthesized into prioritized lists of “quality drivers”
  • Created and refined business processes to integrate quality checks throughout the product creation process, from data ingestion through to delivery
  • Built and coached a team devoted to executing on Quality processes
  • Drove creation of real-time dashboards and metrics that measured our progress along our Quality journey
  • Navigated differentiation by communicating our quality metrics and program to customers and potential customers (e.g. by comparing our output quality vs. what we receive from our suppliers)
  • Prepared materials supporting use of our data for regulatory-grade use cases