Principal Duties and Responsibilities
- Lead research projects aimed at using clinical data to improve healthcare.
- Conceptualize and develop machine learning-empowered products.
- Interface with physicians to help answer important clinical questions based on medical imaging, pathology, and electronic health record data.
- Design frameworks for interfacing between health IT systems and research workflows.
- Work with academic collaborators to understand needs and implement cutting edge algorithms with machine learning.
- Use the Partners HealthCare values to govern decisions, actions and behaviors. These values guide how we get our work done: Patients, Affordability, Accountability & Service Commitment, Decisiveness, Innovation & Thoughtful Risk; and how we treat each other: Diversity & Inclusion, Integrity & Respect, Learning, Continuous Improvement & Personal Growth, Teamwork & Collaboration.
- Other duties as assigned.
- PhD or equivalent combination of experience and education (i.e. Masters degree and 4+ years of experience) in a quantitative field (i.e. engineering, computer science, physics, mathematics)
- 2+ years of experience in data analysis, signal processing, modeling, and machine learning.
- Strong technical skills are a must, including:
- Expert level knowledge in a scripting language such as Python and an object-oriented programming language such as C++
- Familiarity with common tools for data management and analysis including machine learning (i.e. Tensorflow, Theano, Torch), distributed computing (i.e. Hadoop, Spark), database software (SQL or variants), and general scientific computing
- Excellent interpersonal skills to effectively communicate with cross functional teams including staff at all levels of the organization including both technical and non-technical personnel
- Exceptional problem solving and negotiation skills
- Self-motivated, independent and possesses the ability to learn quickly
- Ability to successfully negotiate and collaborate with others of different skill sets, backgrounds and levels within and external to the organization