Senior Data Scientist Redline Lab

Mass General Brigham•Boston, MA

6d•Hybrid

About The Position

Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham. Oversees the informatics architecture and computational scientific programming for a large NIH funded data repository, the National Sleep Research Resource (NSRR). The NSRR supports hundreds of researchers in accessing sleep and other research data through a highly interactive and user-friendly portal linked to powerful analytical and visualization tools within a FAIR environment (Findability, Accessibility, Interoperability, and Reusability). The candidate needs to have excellent computational skills and experience working with large data sets. The role includes extensive data wrangling and cleaning of complex bio signal and other data (both structured and unstructured), utilizing and extending in-house workflows to summarize, visualize, transform and document hundreds or thousands of multi-modal physiological sleep and circadian recordings.

Requirements

Master's Degree Data Science required or Master's Degree Related Field of Study required
Data Science experience with PhD 2-3 years required or Data Science experience with a Master's 3-5 years required
Familiarity with machine learning algorithms, statistical techniques, and data mining methods.
Experience in manipulating large datasets and using databases.
Familiarity with healthcare data sources, such as electronic health records (EHR), claims data, and administrative data.
Understanding of data governance, data quality, and data management principles.
Proficient problem-solving and critical thinking skills, with the ability to analyze complex problems and develop innovative solutions.
Excellent communication skills, with the ability to effectively convey technical concepts to non-technical stakeholders.

Responsibilities

Performs statistical analysis, hypothesis testing, and data modeling on large data sets.
Uses machine learning and AI to solve problems.
Identifies key process drivers when analyzing large datasets.
Performing modeling, forecasting, and programming using Python or other programming languages.
Provides training to junior data scientists and/or analysts.
Participates in meetings with senior leaders when presenting study results.