Statistical Data Analyst (massgeneralbrigham)
Job posting number: #241382 (Ref:RQ4018760)
Job Description
Site: The General Hospital Corporation
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.
Qualifications
This Statistical Data Analyst position works with staff members within the MGH Heart Failure Section who are faculty members at Harvard Medical School and Cardiology Division at MGH. Investigators and analysts work as members of a collaborative multidisciplinary team of clinicians, scientists, and trainees. Under the supervision of a PIs, the selected candidate will lead data analyses for projects related to heart disease and is expected to leverage conventional and advanced data science approaches in the analysis of high-dimensional clinical datasets. Additional responsibilities include developing research protocols, compiling data, managing databases, performing quality assurance, validating programming, and generating outputs and visuals that summarize study results.
The selected candidate will also contribute to the preparation of manuscripts, conference abstracts, grants, and other publications, as well as assist in coordinating collaborative research activities with internal and external investigators. Strong communication skills and the ability to convey statistical concepts in simpler and relatable terms is highly desired.
Additional Job Details (if applicable)
Principal Responsibilities:
• Lead the efficient synthesis and analysis of clinical data for all assigned projects related to cardiovascular disease.
• Participate in study design meetings with internal and external investigators, providing guidance on sample size requirements, approaches to measurement, and clinical endpoints.
• Assist with preparation of IRB submissions and renewals.
• Assist investigators in the development and implementation of statistical analysis plans, ensuring analytical activities are within scope, timeline, and reach the overall aims of each project.
• Participate in the preparation and presentation of study results in manuscripts, conference abstracts, or other publication mediums.
• Coordinate and participate in collaborations with investigators within other Harvard departments and at other institutions across the U.S.
• Participate in and report on assigned project status at bi-weekly team meetings.
• Actively participate in continuing education and mentorship of other research team members.
• Proactively conduct quality control/quality assurance of programming and statistical models, automating processes whenever possible.
Education
A Master's degree in statistics, biostatistics, mathematics, or a related field is required.
Can this role accept experience in lieu of a degree?
No
Experience:
If newly graduating from graduate school, prefer course experience in advanced statistic methods and machine learning.
Knowledge, Skills and Abilities
Position Requirements:
• A Masters degree in statistics, biostatistics, mathematics, or a related field is required.
• Proficiency in biostatistical methods such as quasi-experimental methods appropriate for analysis of complex, observational datasets (claims data, observational cohorts, and clinical trial data); survival analysis; regression; dimension reduction and methods appropriate for clustering and panel data; and machine learning is required.
• Proficiency in oral and written English communication is required.
• Experience and proficiency in one or more of the following statistical programming languages is required: Python, R, SAS, NCSS, MPlus, SPSS, and Stata.
Skills/Competencies that are highly desired:
• Experience and proficiency in prioritizing tasks and requesting support (when needed) while adhering to project deadlines is highly desired.
• An ability to convey complex statistical concepts to a diverse team of clinical professionals with a varying levels of expertise in statistics is highly desired.
• Experience in new machine learning platforms such as Tensorflow, Keras, Pytorch is highly desired.
• Experience in econometric statistical techniques including instrumental variables methods and regression discontinuity is highly desired.
Remote Type
Work Location
Scheduled Weekly Hours
Employee Type
Work Shift
EEO Statement:
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership “looks like” by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.