The Machine Learning Scientist will support a diverse set of initiatives to improve patient selection, treatment and follow-up via the development of novel machine learning & AI algorithms.
You will partner with internal and external stakeholders to develop insights and models to advance discoveries in mental health care.
Roles and responsibilities
- Provide expertise company-wide on a variety of Machine Learning and AI topics in order to improve the patient journey and provide mission-critical applications as COMPASS grows
- Develop algorithms & methodologies that incorporate digital and traditional biomarkers (voice, vision, smart device, etc.) in order to improve the treatment process
- Work collaboratively with engineering (back-end/front-end/UI+UX/ and others) to deploy these algorithms in a highly scalable and distributed infrastructure to help patients in real time
- Communicate insights with stakeholders with the ability to extract therapeutic intelligence by leveraging external and internal data sources
- Work closely with stakeholders to identify quantitative and technological needs for various COMPASS projects
Detailed responsibilities/accountabilities
- The position reports to the VP of Digital Health Research
Profile
- Substantial experience in the field either through industry and/or academia. Biotech & start-up experience a strong plus (Degree in: Statistics, Computer Science, Neuroscience, Engineering, Mathematics, Physics or related)
- Strong analytical, project management, written and verbal communication skills
- Proficient in Python (scikit-learn, numpy, pandas, matplotlib, scipy) and experience with Tensorflow/Keras and/or Pytorch
- Deep experience with at least one of the following: Computer Vision, Natural Language Processing, time-series signal processing, audio signal processing.
- Understanding of at least 2-3 common machine learning & AI architectures (convolutional neural nets, reinforcement learning, attention & transformer-based networks, graph neural nets, generative adversarial networks, etc.)
- Comfortable with Linux and the AWS cloud environment
- Ability to operate independently and in cross-functional teams in an entrepreneurial and rapid growth-oriented environment
- Strong alignment with core company mission and values; Compassionate, Bold, Rigorous, and Inclusive
- Ability to work in the UK or US
Additional qualifications – preferred
- A PhD in a computational field (Degree in Statistics, Computer Science, Neuroscience, Engineering, Mathematics, Physics or related)
- Industry experience in a machine learning or AI role within a digital health organisation, pharma, or biotech
- Experience in R (tidyr, dplyr, ggplot2, Rstudio)
- Background in EEG, fMRI, and other brain measurement technologies a strong plus
- Familiar with R Shiny and/or other app development technologies such as Django/Angular/Clojure