Data Scientist, PREDDICT Project

Mass General Brigham•Boston, MA

1d•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. We are seeking an exceptional Data Scientist to play a central analytic role in PREDDICT, a next-generation clinical and research program at Spaulding Rehabilitation. Focused on predicting, preventing, and improving long-term health and wellness outcomes across high-risk populations, PREDDICT brings together precision rehabilitation medicine, data science, and digital health to redefine how injury and recovery are understood and treated—extending not only lifespan, but HealthSpan, the period of life spent in good health. Rehabilitation settings care for people with life-changing injuries such as brain injury, stroke, burns, spinal cord injury, and limb loss. PREDDICT leverages electronic health records and advanced analytics, including machine learning, to infuse data-driven decision-making into care during a pivotal time in patients’ lives. The program integrates clinical care, longitudinal research, advanced analytics, and system-level implementation to move beyond siloed studies and toward scalable, real-world impact. This role will build the foundation of that mission. The Data Scientist will hold and grow expertise in the Mass General Brigham (MGB) electronic health record (EHR) including an understanding of key rehabilitation data elements, their location in the EHR, and documentation workflows. They will work closely with physician-scientists, clinical teams, research staff, and external partners to guide responsible data utilization throughout the lifecycle from extraction through visualization. It is an opportunity to help 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. About the HealthSpan Lab: The HealthSpan Lab is committed to advancing our understanding of lifelong health. We study the biological, behavioral, and environmental factors that influence healthy aging and long-term function. Our research aims to uncover early markers of decline, identify mechanisms of resilience, and develop interventions that can prevent disease before it begins. By generating evidence across systems and stages of life, we work to improve health outcomes and promote lifelong well-being. About the Rehabilitation Outcomes Center at Spaulding (ROCS): The Rehabilitation Outcomes Center at Spaulding is a central hub for researchers, clinicians, and the broader rehabilitation community advancing data-powered care across the full rehabilitation journey—from hospital to home. ROCS offers robust infrastructure for collaboration among investigators, clinicians, and people with lived experience, supported by platforms such as podcasts and open scientific meetings. With an emphasis on Learning Health Systems, ROCS facilitates access to electronic health record analytics, standardized outcome measures, and implementation science expertise, while also offering mentorship and operational support to investigators through its established partnerships and training programs. We make rehab data smarter and better connected so care decisions are based on solid evidence and personalized to the individual.

Requirements

Bachelor's Degree Related Field of Study required or Master's Degree Related Field of Study preferred
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

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.