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Yale University

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Yale University, New Haven, CT, USA

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"Data Scientist"

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Data Scientist

Overview

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.

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 containerized environments.

The CarDS lab is a multidisciplinary group of junior faculty, postdoctoral trainees, and graduate and undergraduate students across Yale. We collaborate with informatics, computer science, and statistics groups at Yale and several leading institutions nationally and internationally. We have developed novel tools to measure and improve care quality using data from electronic health records and software solutions for the early diagnosis of cardiovascular disorders. Our research offers unique collaborative opportunities with industry, health systems and health technology partners. For more information, please visit CarDS Lab.

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 Skills and Abilities

  1. Expertise working with Linux, Python, and Java.
  2. Ability to work with large structured and unstructured datasets, and GPU-accelerated computing. Proven experience with Large Language Models.
  3. Sound background in theoretical and applied machine learning/deep learning with applications to either language, signals, or images.
  4. Demonstrated strong ability to communicate technical ideas and results to non-technical customers in written and verbal formats.
  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

  1. Master’s degree in computer science, applied/computational mathematics, engineering, biostatistics, statistics, and hands-on experience in deep learning or a PhD in any of the previously mentioned fields.
  2. Proven experience in leading conference publications, particularly in the deep learning field.
  3. Strong background in data analysis with a diverse set of platforms, such as Python and/or R.
  4. Knowledge of advanced analytic approaches, including signal processing, image analysis, supervised and unsupervised machine learning, and deep learning.
  5. Interest in leading a large, dynamic group of individuals with an interest in a career in healthcare innovation.

Principal Responsibilities

  1. Extract huge volumes of data from multiple internal and external sources.
  2. Conduct undirected research and frame open-ended industry questions.
  3. Employ sophisticated analytics programs, machine learning and statistical methods to prepare data for use in predictive and prescriptive modeling.
  4. Thoroughly clean and prune data to discard irrelevant information.
  5. Explore and examine data from a variety of angles to determine hidden weaknesses, trends and/or opportunities.
  6. Devise data-driven solutions to the most pressing challenges.
  7. Invent new algorithms to solve problems and build new tools to automate work.
  8. Communicate predictions and findings to management and IT departments through effective data visualizations and reports.
  9. Utilize real-time data streams to generate predictive and prognostic analytical outputs.

Required Education and Experience

Bachelors’ degree in computer science, mathematics or a related subject and six years of experience, or an equivalent combination of education and experience.

Salary Range
$92,000.00 - $146,750.00

Location: New Haven, Connecticut

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