Data Scientist

Built and based in Austin, Texas, we are a small but mighty team of “Closers” who are passionate about changing the future of healthcare. With numerous accolades in our trophy case, we have been repeatedly recognized by the Austin Business Journal as a “Best Places to Work” and Built In as a “Best Startups” for our culture and employee-centric programming. We believe in empowering our teams to do their best work, offer generous employee benefits that include 100% paid medical insurance for employees and their dependents, flexible PTO, paid parental leave, 401k, and ongoing learning and team building opportunities.

We believe that diverse teams are stronger teams and understand that building for the future includes embracing and honoring different backgrounds and experiences. Doing so creates the foundation for our ability to build systems that drive unbiased outcomes.

We strive to create a supportive team high in rigor, with a constant improvement mindset. We believe that teams high in trust innovate faster and better, collaborate more effectively, and love their work more. If this sounds like a place where you can see yourself building for a future that transforms healthcare, we’d love for you to join us!

About the Role:

Are you passionate about leveraging data science to revolutionize healthcare outcomes? We're seeking a skilled Data Scientist to join our team, where you'll spearhead the development of predictive models using cutting-edge machine learning and statistical methodologies via the Closed Loop platform. Your mission will be to collaborate closely with healthcare stakeholders, uncovering key business challenges and tailoring analytical solutions to drive impactful results.

From optimizing resource allocation to improving patient outcomes, your expertise will be instrumental in transforming complex healthcare data sets into actionable insights. If you're ready to make a difference in healthcare by translating data into tangible improvements, join us in this exciting role.

What you'll do:

• Develop predictive models to forecast healthcare trends, optimize resource allocation, and improve patient outcomes, utilizing machine learning and statistical methodologies via the Closed Loop platform.
• Collaborate closely with healthcare stakeholders to identify key business challenges and opportunities, designing customized analytical solutions to address their specific business needs.
• Deliver clear and compelling presentations and reports to communicate findings and recommendations to diverse audiences, including executives, clinicians, and technical teams, fostering understanding and driving actionable outcomes.
• Utilize the Closed Loop platform to clean and validate diverse healthcare data sets, including but not limited to claims, medical records, laboratory results, and ADT information, ensuring data integrity and reliability.
• Provide training and guidance to customer data scientists, equipping them with best practices and methodologies tailored specifically for data science healthcare.

Qualifications & Skills

• Bachelor's degree or higher in a quantitative field such as statistics, computer science, mathematics, or a related discipline, with a focus on healthcare applications.
• Demonstrated experience in applying data science techniques to healthcare datasets, including proficiency in Python and SQL.
• Strong analytical and problem-solving skills, with the ability to translate complex healthcare challenges into well-defined analytical tasks and deliver actionable insights and recommendations.
• Excellent communication skills, both verbal and written, with experience presenting technical findings to non-technical stakeholders and tailoring messaging to different audiences.

Bonus Qualifications

• Expertise in advanced statistical methodologies tailored for healthcare applications, such as pharmaceutical medical economics or actuarial experience
• Completion of a Master's or Ph.D. program in computer science or a healthcare-related field, indicating a solid foundation in both technical and domain-specific knowledge.
• Experience working effectively in multidisciplinary teams fostering positive client relationships.

Why…