Data Scientist at Buoy Health

Job to be done
We’re the best way to get better.

About Buoy Health:
At Boston-based Buoy, you can join a work-from-wherever team that empowers people to choose the best care for their health needs. Developed out of the Harvard Innovation Labs by a team of doctors and data scientists, Buoy leverages its AI to understand peoples’ symptoms and then guide them to relevant care options within Buoy’s care marketplace, where people are free to select the option that feels best for their situation. Buoy also works with employers, health plans, and health solutions to simplify and streamline accessing covered care options.


Compensation: $120,000-150,000 annually

About the Role:
Buoy is on a mission to build the most robust destination for managing health needs. By pairing our AI navigation capabilities with an agnostic marketplace of third-party health solutions and care providers, we are matching people with the best care for their unique situation. One of Buoy’s greatest differentiators is leveraging our machine learning algorithms to intake users’ symptoms and provide a potential diagnosis and triage recommendation. As a Data Scientist at Buoy, your core responsibility is to solve problems intelligently and creatively. You will work with Buoy’s product and medical teams to improve the way users find and engage with care through Buoy. You will apply both classical and modern machine learning techniques. You will formulate hypotheses and design experiments to evaluate them. You will develop, specify, and implement validation methods that scale and ensure that other teams are empowered to do the same. You will communicate insights about user behavior, agent behavior, data quality, and data completeness to different teams across the company. To be successful, you must have a keen interest in data-driven decision making and helping people make better decisions about their health.

Responsibilities:
Implement data-driven solutions to improve the way Buoy’s users engage with care through Buoy
Work with our product and engineering teams to productize models and services
Design and validate experiments to test models and solutions
Advise on A/B testing best practices
Turning complex data sets into actionable insights to drive product performance
Gather, process, and analyze data to support research
Synthesize and communicate insights to the whole company
Define, evaluate, and monitor key metrics and understand the root cause of changes

About You:
BS in Computer Science, Statistics, or related, or equivalent experience
3+ years related work experience
Programming experience in Python, C/C++ or Java (3+ years)
Professional experience in a quantitative analysis field (2+ years)
Good written, spoken, and visual communication skills
Ability to formulate effective hypothesis and design experiments
Ability to define relevant metrics that can serve as appropriate and accurate measurements and lead to actionable insights
Experience with machine learning techniques
Experience in e-commerce AND healthcare
Bonus Points for the following experience:
Graduate degree in Computer Science, Statistics, or related
Experience with machine learning applications to e-commerce
Experience in personalization and consumer behavior
Familiarity with data visualization techniques
Experience with Bayesian networks

Benefits:
Medical, dental, and vision
401k with company match
Stock options
Generous unlimited vacation policy
L&D reimbursement policy
Work from Wherever—Buoy is remote first, with employees located across the US
Time off for major holidays, including the last two weeks of the year

Equal Opportunity Employer Statement:At Buoy, we are united by our commitment in guiding people to the right care. And we believe it takes a workforce that nurtures difference to get the job done. Buoy champions inclusion. We encourage applicants of all ages, races, ethnicities, colors, national origins, genders, gender identities and gender presentations, sexual orientations, disabilities, veteran status, and other characteristics that make a person unique. We are proud to be an equal-opportunity employer, and to be a part of a team that prioritizes diverse points of view. 

**This role is located in the United States. Unfortunately, we are unable to support international applicants at this time.