Junior Machine Learning Scientist

Develop, optimize and train machine learning models to improve patient care and provide efficiency gains in the clinical workflow.

• Effectively communicate with shareholders of a project

• Publish interesting and novel results in both machine learning and clinical communities.

• Develop tooling to facilitate model development in a healthcare setting.

• 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

Strong sense of urgency and proactiveness

• Ability to function effectively and independently in a fast-paced environment, organize and prioritize work independently, and meet tight deadlines

• Self-motivated, with an entrepreneurial mindset and ability to learn quickly

• Strong analytical, planning, organization and time management skills with a high attention to detail

• Excellent interpersonal skills to effectively communicate with technical teams, cross-functional teams, and staff at all levels of the organization including both technical and non-technical personnel

• Ability to relate to and gain insights from product end users

• Excellent and succinct written and oral communication skills

• Ability to effectively conduct meetings and lead and facilitate large working sessions with all levels of staff and across various stakeholder groups

• Strong decision making skills, with the ability to negotiate/balance decisions and priorities across functions; comfort making hard decisions with incomplete data and in a timely manner

• Demonstrates strong evidence of algorithmic and structured thinking, and intuition for logic, pattern matching, what-if analysis, problem decomposition. and synthesis

• Demonstrates ability to organize and incorporate complex systems requirements into product features and prioritize features effectively

• Strong background in machine learning

• Capable to quickly learn new knowledge (new algorithms, architectures, models and optimizations etc)

• Capable to code in Python or another programming language (with a willingness to learn Python)

• Highly comfortable with traditional machine learning algorithms (e.g., SVM, boosting, bagging, etc.)

• Comfortable working independently and defining measurable, achievable goals

• Interest in developing machine learning models in a research and commercial setting