Deep Learning Data Scientist
We are a human-centered digital health company that seeks to radically improve brain health outcomes by leveraging cutting-edge technology and machine learning to unlock precision brain health for as many people as possible. While we are steadfastly focused on individuals’ brain health, we believe that meaningful outcomes can only be achieved within an ecosystem of care that actively includes and engages physicians, professionals and caregivers. We are a team of 30+ and are embarking on an exciting period of accelerated growth, and invite qualified, collaborative, self-driven and impact-oriented professionals to join our dynamic and fast-growing team.
We are looking for a data scientist who is willing to take on new challenges and work in a highly collaborative environment with clinicians, developers, and other data scientists. There is always something new to learn, and the team both supports and challenges each other so that the best solutions win. This role is core to the product vision and continued growth of Linus Health.
- learn, apply, and innovate on machine learning algorithms from feature engineering to evaluation with a focus on deep learning
- systematically investigate statistical and algorithmic approaches to make data driven decisions and achieve accuracy and explainability
- address data challenges such as missing data, class imbalance, small data sizes, and inconsistent formatting
- collaborate with clinicians, product managers, and software engineers to develop applied solutions and prioritize research
- lead initiatives and mentor junior scientists
- learn and evaluate new machine learning frameworks
- collaborate effectively and learn from other data scientists to align on best practices and leverage existing tools and knowledge
- clearly document, track, and communicate results
- participate with the team on publications and research to promote Linus Health as a thought leader in the domain of healthcare AI
Skills and Qualifications
- PhD and 2-3 years experience, Masters and 3-5 years experience
- degree preferred in Computer Science, Statistics, Math or equivalent
- experience applying deep learning techniques for image, video, and time-series analysis
- deep knowledge of different deep learning network architectures and their tradeoffs including LSTM, GRU, CNN, RNN, different pooling methods, different activation functions, etc.
- understanding of key deep learning techniques such as transfer learning, drop out, etc. as well as different
- use of core statistical methods such as correlation analysis, hypothesis testing, evaluating distributions, etc.
- familiarity with data imputation methods using deep learning such as generative adversarial networks
- strong communication skills; ability to simplify complex concepts
- experience with programming in languages such as Python
- strong publication record
- experience with AWS SageMaker and related tools
- expertise in software development
- experience in healthcare
What We Offer
- an opportunity to have a lasting impact on the way people and communities engage with brain and mental health, and even to affect the prognosis of people’s mental and brain health trajectory
- experience-based market salary & benefits
- an exciting, dynamic start-up atmosphere
- a flexible work environment around hubs in Boston, San Diego, and Toronto (remote applicants will be considered)