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.