West Coast (Hybrid Work Environment) · Full time
We are Gabbi.
We are on a mission to do away with delayed diagnosis. We have created a proprietary machine learning model that can predict breast cancer 2 years before it is diagnosed. We have validated our model with a national health insurance company and need someone to lead the development of our consumer-facing application. Combining the power of our AI model with consumer-centric design and usability to create an engaging experience.
Most people will have been impacted by breast cancer at 50, either through a direct diagnosis, or by the diagnosis of a loved one. Unfortunately, breast cancer is affecting women at a younger age - 85% of whom are underdiagnosed or diagnosed too late because of a lack of recommended breast cancer screens.
I would know, my Mom was one of them-- and so was I. My name is Kaitlin Christine, and I am the CEO & Founder at Gabbi.
At Gabbi, we save lives.
We’re looking for an experienced Data Scientist who is passionate about decreasing delayed diagnosis of breast cancer and believes AI is the key!
What you will do
This Data Scientist will design and construct Gabbi’s scalable risk prediction engines while working with a team of biomedical informaticians, clinicians, engineers, and other experts. This hire will bring the most creative and cutting edge biomedical research, and statistical, machine learning, and NLP approaches to risk detection in healthcare to life. This involves understanding the granular mathematics behind model experimentation to a larger scalable risk prediction algorithm. This opportunity requires a thorough technical skillset, willingness to ‘get in the weeds’, and creative drive to keep Gabbi at the precipice of interdisciplinary inventions in cancer early detection and prevention.
In this role, you will be responsible for:
- Quickly testing early risk prediction models, model assumptions, and iterate to improve the accuracy of our existing risk models
- Work closely with our biomedical, clinical, and scientific experts to develop risk prediction models using medical records and related data. This includes developing ML/AI/and NLP based models from scratch.
- Work closely with our biomedical informatics team to ensure biological and clinical viability of our risk prediction models
- Publish and patent relevant innovations and risk prediction tools
- Determine appropriate computational environments (hardware and softwares) for projects
- Condensing user results into viable feedback for the team in the format of presentations, documentation, and timely periodic updates.
- Translating all results and methods to a variety of team members.
- Work closely with our biomedical and UX experts to use quantitative and qualitative methods to summarize user results. This includes designing the backends for statistical dashboards.
Who you are:
- You are analytical & organized
- You are creative and resourceful
- You are highly empathetic and fiercely focused on delighting customers
- You are an excellent communicator and a collaborative team player
- You have “strong convictions, loosely held” and are always open to being wrong
- You are an overachiever who acts with urgency and gets shit done!
- Prior experience holding a role in data science capacity required
- Prior experience in bioinformatics required
- Prior experience working with Claims Data and electronic health records preferred
- Prior experience with Natural Language Processing required
- Prior experience with cancer biology and risk factor prediction preferred
- Prior early stage start-up experience preferred
- Prior experience with biomedical research
- 3+ years experience in a startup environment in a data science role
- Data Science expertise
- Background or Higher Education in Bioinformatics, Computational Biology, Applied Math, Statistics, and ML, or equivalent fields
- Publication or grant writing experience
- Track record of success in a fast-paced, agile organization
- Experience building a ML/AI/NLP model from inception to its launch (even if it’s a new product within a larger company)
- Strong experience with R, python, Linux/Unix, shell scripting
- Experience with AWS, Azure, or Google Cloud services
- Strong experience with version control and project organization (git, github, and related)
- Experience with structured and unstructured data processing and analysis
- Experience with ‘big data’
- Strong technical chops and high communication skills, an ability to translate complex engineering solutions for non-technical teams
- Experience fostering an inclusive team culture and a diverse team to surface the best talent and ideas
What you will do:
This is an incredible opportunity to join a venture backed, early stage startup as full time employee #5. You will drive the development of our core product: the Gabbi Risk Assessment Model (GRAM). You will work side by side with the CEO, the Head of Engineering, and Lead Data Scientist, as well as engineers and designers. Your goal is to help us iterate on our risk model so that women of all ages and ethnicities can learn their risk for breast cancer.
We are a hybrid workforce. You have the opportunity to work remotely with minimum traveling requirements for Quarterly Team Offsites!
Competitive market salary and/or equity compensation. Competitive healthcare coverage including health, dental, and vision. Hybrid work environment.
Equal Employment Opportunity
The responsibilities and duties of this position described here are representative of those an employee must perform. This is not a comprehensive list and other duties may be assigned.
We are an Equal Employment Opportunity ("EEO") Employer. It has been and will continue to be a fundamental policy of Gabbi not to discriminate on the basis of race, color, creed, religion, gender, gender identity, pregnancy, marital status, partnership status, domestic violence victim status, sexual orientation, age, national origin, alienage or citizenship status, veteran or military status, disability, medical condition, genetic information, caregiver status, unemployment status or any other characteristic prohibited by federal, state and/or local laws. This policy applies to all aspects of employment, including hiring, promotion, demotion, compensation, training, working conditions, transfer, job assignments, benefits, layoff, and termination.