Senior Data Scientist, Qventus

• 3+ years of relative industry experience developing, launching, and maintaining ML systems in production at scale
• 1+ years experience developing and tuning LLM systems
• Strong cross-functional communication with technical and non-technical partners
• Hands-on data engineering experience manipulating data sets, data cleaning, and pipelines with strong coding skills in Python and SQL
• Strong software development foundations - dedication to high code quality, stable architecture

Desirable

• We’re looking for an experienced Data Scientist to join our Data Science team
• In this role, you will leverage your expertise to develop and implement cutting edge solutions leveraging a wide range of machine learning, statistical, and other mathematical optimizations
• You will evaluate potential modeling approaches, implement and operationalize algorithms with your fellow data scientists and product teams, and drive meaningful advances to the quality and breadth of our ML & LLM solutions to boost Qventus intelligence and outcomes
• You’ll work cross-functionally with clinicians, data scientists, data platform engineers, and product experts to shape solutions that deliver measurable value
• This is a high-impact role that will influence our models and products that improve the quality of healthcare and save patient lives, strengthen customer outcomes, and shape our company’s growth trajectory
• Build, refine, and maintain statistical and machine learning models at scale, including NLP and explainable AI approaches
• Develop, tune, and deploy LLM systems with an eye towards rigorous evaluation of performance and user trust
• Design comprehensive experiments and devise impactful analytics to measure the net impact of AI in healthcare settings
• Perform hands-on data engineering: cleaning, transforming, and building pipelines (SQL, Python)
• Collaborate with cross-functional teams to translate data insights into deployed products
• Strong ability to communicate findings clearly to both technical and non-technical audiences