Website Buoy Health
We create technology with heart for the health of every person in the world.
Buoy builds a digital health tool that helps people – from the moment they get sick – start their health care on the right foot. Started by a team of doctors and computer scientists working at the Harvard Innovation Laboratory in Boston MA, Buoy was developed in direct response to the downward spiral we’ve all faced when we attempt to self-diagnose our symptoms online. Buoy leverages artificial intelligence – powered by advanced machine learning and proprietary granular data – to resemble an exchange you would have with your favorite doctor – to provide consumers with a real-time, accurate analysis of their symptoms and help them easily and quickly embark on the right path to getting better. Buoy is based in Boston and was founded in 2014.
The Director of AI will work closely with the CTO, data scientists, physician researchers, and product owners, across all aspects of the business, to provide data-driven insights and introduce AI-based product solutions. The director will oversee the design and implementation of data collection processes to ensure high-quality experiments and analyses and to enable future data-driven solutions. The director will establish a data strategy and advocate for good research in all aspects of the business. The director will manage a team of data scientists and physician researchers. The director will collaborate with other business leaders. While necessary, the director will also work as a contributor, performing data analyses and developing models.
— Work closely with research and engineering teams to design, develop, and incorporate AI solutions into new and existing products
— Plan and design AI projects: specifying the problem, guiding the project scope and methods for tracking progress
— Mentor researchers and engineersExplore new data sources and discover techniques for best leveraging data
— Constantly review relevant literature to identify emerging methods or technologies and current best practices
— An MS or Ph.D. in a related field, such as Computer Science, Mathematics, Statistics, or Physics
— Significant doctoral or post-doctoral research experience, or 5 or more years of work experience in AI research projects
— Experience leading teams, running projects, and mentoring staffFamiliarity with modern ML frameworks and tools
— Strong coding abilities in Python and/or C/C++
— Good communication skills and an awareness of how to communicate data and results effectively
— Comfort working in new, ambiguous areas, where learning and adaptability are key skills
— Experience working with large datasets
— Solid background in statistical methods for Machine Learning, e.g., Bayesian methods, HMMs, Graphical Models, dimensional reduction, clustering, classification, regression techniques, etc
— Strong familiarity with Deep Learning techniques, e.g., network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies, etc.
— Experience with healthcare datasets
— Experience with applications of AI in medicine
— Experience with causal models