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Data Scientist

Job Description


Internal Medicine - Cardiology


University Job Title

Data Scientist 1

Bargaining Unit

None - Not included in the union (Yale Union Group)

If Fixed Duration, Period

2 years from date of hire

If Fixed Duration, is continuation possible?


Other Fixed Duration Date


Compensation Grade

Administration & Operations

Compensation Grade Profile

Manager; Program Leader (24)

Wage Ranges

Click here to see our Wage Ranges

Work Location

Medical School Campus

Worksite Address

195 Church Street
New Haven, CT 06510

Work Week

Standard (M-F equal number of hours per day)

Searchable Job Family

Computing and Information Systems, Medical Facilities, Research/Support

Total # of hours to be worked:


Position Focus:

The Cardiovascular Data Science (CarDS) Lab at Yale University has an opening for a Data Scientist to participate in a series of projects that focus on leveraging healthcare data to improve patient care. The work spans work with structured and unstructured data in the electronic health record (EHR), with the opportunity to work on applications of machine learning/deep learning in novel areas of healthcare. The position is open for a driven individual with either a master’s or doctoral training in data science, computer science, or a similar background with some experience working with large datasets. Prior experience with healthcare is not required but will be helpful. The ideal candidate will have an interest in broad career development in a dynamic environment that allows them to develop as a leader in healthcare data science and innovation.

The team at CarDS lab represents a multidisciplinary and exciting group of postdoctoral trainees and graduate and undergraduate students across Yale, with broad collaboration with informatics, computer science, and statistics groups at Yale and at several leading institutions nationally. There will also be a close collaboration with the Yale/Yale-New Haven Hospital Center for Outcomes Research and Evaluation (CORE). The team at CarDS Lab has developed novel tools to measure and improve the quality of care using data from the EHR and software solutions for the early diagnosis of several cardiovascular disorders. The research in the lab allows unique collaborative opportunities with industry and health technology partners.

Under the direction of the Principal Investigator, the ideal candidate will perform a variety of duties involving the development of data and analytic pipelines for research studies and will work as a member of a research team to provide input in the design of the study, perform data analysis, and lead or assist drafting analytical sections for peer-review publication for various projects. The candidate is expected to lead several efforts, including working with the team to develop, discover and apply novel machine learning applications to healthcare. Responsibilities will also include participating in the design, implementation, and maintenance of data pipelines and leading/assisting in building algorithms for deep learning with close collaboration from the study team.

While programming experience with Python and/or R is required, experience with one or more of the following skills will be an asset. However, if the individual is willing to learn these skills, there are opportunities to learn them in this position: distributed and cluster computing, with a specific focus on PySpark, working with large tabular data with python/R, basic principles of natural language processing and their applications in python with PyTorch/Huggingface/SpaCy, applications of computer vision and signal processing in Tensorflow or PyTorch, and the ability to deploy and work in ized environments.

Essential Duties

Develop and execute new and/or highly complex algorithms and statistical predictive models and determine analytical approaches and modeling techniques to evaluate potential future outcomes. Establish analytical rigor and statistical methods to analyze large amount of data, using advanced statistical techniques and mathematical analyses.  Manage analytical projects from data exploration, model building, performance evaluation, through implementation. Develop work plans and monitor progress and project timelines. Document coding and changes to work plans using established work group methods in GitHub. Interact with a multidisciplinary team of internal and external peers to regularly, effectively, and openly communicate progress and outcomes of planned work. Attend weekly team meetings to discuss team and project-related activities, issues, change, communications, and updates.

Required Education and Experience

Master’s Degree in computer science, applied/computational mathematics, engineering, biostatistics, statistics, or a quantitative field such as astronomy or geology, and 2 years of hands-on experience in deep learning or an equivalent combination of education and experience.

Required Skill/Ability 1:

Expertise in working with Linux and Python.

Required Skill/Ability 2:

Ability to work with large structured and unstructured datasets, and GPU-accelerated computing.

Required Skill/Ability 3:

Sound background in theoretical and applied machine learning/deep learning with applications to either language, signals, or images.

Required Skill/Ability 4:

Demonstrated strong ability to communicate technical ideas and results to non-technical customers in written and verbal formats.

Required Skill/Ability 5:

Strong organizational, time management, and leadership skills. Ability and willingness to work in a highly collaborative team environment and matrixed organization.

Preferred Education, Experience and Skills:

Experience leading conference publications, particularly in deep learning field. Strong background in data analysis with a diverse platforms, such as Python and/or R. Knowledge of advanced analytic approaches (signal processing, image analysis, supervised and unsupervised machine learning, and deep learning). Interest in leading a dynamic group, with an interest in healthcare innovation.

Weekend Hours Required?


Evening Hours Required?


Background Check Requirements

All candidates for employment will be subject to pre-employment background screening for this position, which may include motor vehicle, DOT certification, drug testing and credit checks based on the position description and job requirements. All offers are contingent upon the successful completion of the background check. For additional information on the background check requirements and process visit "Learn about background checks" under the Applicant Support Resources section of Careers on the It's Your Yale website.

COVID-19 Vaccine Requirement

Thank you for your interest in employment at Yale University. Please also note that the university has a COVID-19 vaccination and booster requirement for all students, staff & faculty which is described in the COVID-19 Vaccine Program. As you search our open positions, you will see that all postings list their on-site addresses which gives more detail on the on-campus work location of the role.

Posting Disclaimer

The intent of this job description is to provide a representative summary of the essential functions that will be required of the position and should not be construed as a declaration of specific duties and responsibilities of the particular position. Employees will be assigned specific job-related duties through their hiring departments.

EEO Statement:

University policy is committed to affirmative action under law in employment of women, minority group members, individuals with disabilities, and protected veterans. Additionally, in accordance with Yale’s Policy Against Discrimination and Harassment, and as delineated by federal and Connecticut law, Yale does not discriminate in admissions, educational programs, or employment against any individual on account of that individual’s sex, sexual orientation, gender identity or expression, race, color, national or ethnic origin, religion, age, disability, status as a special disabled veteran, veteran of the Vietnam era or other covered veteran.

Inquiries concerning Yale’s Policy Against Discrimination and Harassment may be referred to the Office of Institutional Equity and Accessibility (OIEA).

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100 Wall Street, New Haven CT 06511




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