Senior Data Scientist

at  Qventus

ABOUT US:

Qventus is a real-time decision making platform for hospital operations. Our mission is to simplify how healthcare operates, so that hospitals and caregivers can focus on delivering the best possible care to patients. We use artificial intelligence and machine learning to create products that help nurses, doctors, and hospital staff anticipate issues and make operational decisions proactively.

ABOUT THE ROLE:

Qventus is looking for a Senior Data Scientist to help power the next generation of Qventus’s AI in our Inpatient solution. You’ll join a cross-functional team of clinicians, data scientists, data platform engineers, and product experts to help support optimized discharge planning and operations to get patients the right care faster and more efficiently across the country.
As a Senior Data Scientist 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 solutions to boost Qventus intelligence and outcomes. You should be strongly motivated to impact 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.

KEY RESPONSIBILITIES:

• Solve operational challenges in healthcare through the development, operationalization, and tuning of impactful models developed thoughtfully using a variety of machine learning, 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