Data Scientist, Qventus

• 3+ years of research experience using a wide variety of statistical and machine learning techniques - particularly in NLP, explainable ML (Python)
• 2+ years of relative industry experience developing, launching, and maintaining machine learning systems at scale
• 1+ years experience developing and tuning LLM systems (strong experience with RAG preferred)
• Strong cross-functional communication with technical and non-technical partners
• Hands-on data engineering experience manipulating data sets, data cleaning, and pipelines (SQL, Python)
• Strong software development foundations - dedication to high code quality, stable architecture, and an eye toward maintainability

Desirable

• As a Senior Data Scientist / LLM Engineer at Qventus, you will have the opportunity to explore Qventus’ unique and rich healthcare dataset to develop cutting-edge solutions that leverage a wide range of machine learning, statistical, and other mathematical optimizations
• You will evaluate potential modeling approaches, build features, 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 should be strongly motivated to have an impact in the company and dedicated to helping improve the quality of healthcare and patient outcomes. What we do can meaningfully change and, in some cases, save lives
• Solve operational challenges in healthcare through the development, operationalization, and tuning of impactful models developed thoughtfully using a variety of machine learning, LLM, mathematical, and statistical approaches
• Collaborate with Product and Clinical partners to investigate, assess, and deploy POC solutions in strategic business areas
• Design comprehensive experiments and analytics to measure the net impact of our interventions in healthcare settings
• Create tools and resources to improve transparency in Data Science technical architecture and increase collaboration with engineering and analytics partners