Gabbi, Inc. Fractional Data Scientist Intern Remote · Intern

Apply for Fractional Data Scientist Intern

Have you ever been impacted by breast cancer? Do you know somebody who has? By the time we turn 50, most of us will have been close to somebody who has had a diagnosis or even been diagnosed ourselves. At Gabbi, we’re on a mission to make late-stage breast cancer obsolete.

Early detection is key. Women diagnosed at stage 0 or stage 1 have a 99% survival rate; women diagnosed at stage 4 have a ~30% survival rate.

The problem is that women don’t know their risk, so they don’t know what kind of care to get and when to get it. Gabbi ensures every woman knows her risk with our consumer facing risk assessment and democratizes access to breast specialists via telehealth in order to get women to the right care at the right time.

We imagine a world where every woman knows her risk, and we won’t stop fighting until we get there. At Gabbi, we save lives. Do you want to save lives too?

What You’ll Do:

Risk Assessment Model Management:

• Ensure the standard of care licensed risk assessment model remains compliant within our platform
• Implement updates and maintain the model's accuracy and reliability

GRAM Development and Implementation:

• Oversee the execution of our proprietary risk assessment model, the GRAM, on patient-reported data
• Continuously refine and improve the GRAM algorithm based on new research and data insights

Research, Grants, and Publishing:

• Design and conduct studies to validate and improve the GRAM
• Write and publish peer-reviewed papers on the GRAM's effectiveness and applications
• Design studies with co-collaborators including writing grants, submitting for IRB approval, and running that process
• Conduct ongoing research to enhance the GRAM's predictive capabilities
• Stay up-to-date with the latest advancements in breast cancer risk assessment and machine learning

Risk Assessment Strategy:

• Develop and maintain the logic for determining when to use the standard risk assessment model versus the GRAM
• Optimize the integration of both models to provide the most accurate risk assessments

Qualifications:

• Ph.D. or Master's degree in Data Science, Computer Science, Biostatistics, OR actively working in Masters or Ph.D program
• Proven experience in developing and implementing machine learning models, particularly in healthcare
• Strong background in statistical analysis and predictive modeling
• Proficiency in programming languages such as Python, R, and SQL
• Experience with healthcare data, familiarity with breast cancer risk models is a nice to have
• Excellent scientific writing skills and a track record of peer-reviewed publications
• Ability to work independently and manage multiple projects simultaneously
• Experience working with IRB
• Experience and success winning grants
• Strong communication skills to collaborate with cross-functional teams and present findings to stakeholders