Senior Data Scientist Redline Lab
At a glance
Senior Data Science role at Massgeneralbrigham. Boston-MA · full-time · $93,953–$136,739 base.
dataroles summary, based on the employer's posting.
What you'll do
- Shape informatics architecture and scientific computing for the National Sleep Research Resource data repository
- Clean and reshape structured, unstructured and physiological sleep data using and extending internal workflows
- Apply statistical tests, predictive models and machine learning to large datasets, including forecasting in Python or another language
- Summarize, visualize and document multi-modal sleep and circadian recordings for researchers
- Present study findings to senior leaders and help junior data scientists or analysts build their skills
What you bring
- A master's degree in data science or a related discipline is required; experience cannot replace it
- With a master's degree, you need three to five years in data science; with a PhD, two to three years
- You can work with large datasets and databases and understand machine learning, statistical methods and data mining
- You understand healthcare data, data quality and governance, and can explain technical ideas to nontechnical audiences
Who this fits
This senior role suits a data scientist who enjoys large-scale data wrangling and research computing, particularly with sleep and physiological recordings. The job is hybrid in Boston, with a forty-hour workweek on the day shift. You’ll also train junior colleagues and present findings to senior leaders.
From the employer
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.
Job Summary
SummaryOversees 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.
Does this position require Patient Care?
No
Essential Functions
-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.
Qualifications
Education Master's Degree Data Science required or Master's Degree Related Field of Study required Can this role accept experience in lieu of a degree? No Licenses and Credentials Experience Data Science experience with PhD 2-3 years required or Data Science experience with a Master's 3-5 years required Knowledge, Skills and Abilities - 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.
Additional Job Details (if applicable)
Remote Type
Hybrid
Work Location
221 Longwood Avenue
Scheduled Weekly Hours
40
Employee Type
Regular
Work Shift
Day (United States of America)
Pay Range
$93,953.60 - $136,739.20/Annual
Grade
7
EEO Statement:
0100 Mass General Brigham Incorporated is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran’s Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
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.
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