Data Scientist, PREDDICT Project

Mass General Brigham•Boston, MA

1d•Hybrid

About The Position

Mass General Brigham is seeking an exceptional Data Scientist to play a central analytic role in PREDDICT, a next-generation clinical and research program at Spaulding Rehabilitation. This program focuses on predicting, preventing, and improving long-term health and wellness outcomes across high-risk populations by integrating precision rehabilitation medicine, data science, and digital health. The Data Scientist will be responsible for building the foundation of this mission, gaining expertise in the Mass General Brigham (MGB) electronic health record (EHR), understanding key rehabilitation data elements, and working closely with physician-scientists, clinical teams, research staff, and external partners to guide data utilization from extraction through visualization. This role offers an opportunity to shape how complex clinical data are transformed into insight, prediction, and evidence that directly informs care delivery and long-term outcomes in rehabilitation and disability health. The Data Scientist will work in a highly matrixed environment, collaborating across the HealthSpan Lab, the Rehabilitation Outcomes Center at Spaulding, and MGB Digital. The HealthSpan Lab is committed to advancing the understanding of lifelong health by studying factors influencing healthy aging and long-term function, aiming to uncover early markers of decline, identify mechanisms of resilience, and develop interventions. The Rehabilitation Outcomes Center at Spaulding (ROCS) is a hub for advancing data-powered care across the rehabilitation journey, emphasizing Learning Health Systems and facilitating access to EHR analytics, standardized outcome measures, and implementation science expertise.

Requirements

Bachelor's Degree in a Related Field of Study required
Experience working in data science-type positions and with large data sets (2-3 years preferred)
Ability to create reports and dashboards with Tableau.
Skilled in data analysis with Python and SQL.
Knowledge of statistics.
Knowledge of machine learning.

Nice To Haves

Master's Degree in a Related Field of Study preferred
Preferred SQL database management and administrative knowledge.
Practiced knowledge of numerical optimization algorithms.

Responsibilities

Maintain and grow expertise on rehabilitation EHR data structure, storage and retrieval, and computing processes. Maintain working knowledge of clinical documentation workflows and informatics systems. Educate other team members on these functions.
Design and evaluate predictive models and advanced algorithms for rehabilitation recovery trajectories.
Design, build, and maintain reports and dashboards to convey data insights in real-world clinical and research settings. Ensure visualizations are tailored to meet the specific needs of the rehabilitation community in a Learning Health System framework.
Collaborate with researchers, clinicians, clinical informatics staff, and information systems analysts to design research studies.
Draw conclusions or make predictions, based on data summaries or statistical analyses.
Analyze complex and high-dimensional clinical and operational data for dependencies, patterns, outliers, inaccuracies, and validity.
Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and/or advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries.
Contribute to the design and evaluation of optimal data-driven metrics (such as physician/facility performance criteria, bottleneck metrics, productivity limits, processing delay/error reports, etc.).
Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data.
Generate and test hypotheses and analyze and interpret the results.