How to Apply
A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
Note: Remote or Hybrid work arrangement options are available for this position
Summary
Are you wicked smart? Do outer joins and random forests make you giddy like when you were a kid at the toy store? Do we ever have a position for you! We are in search of a Senior Data Scientist/Machine Learning (ML) Specialist to develop predictive analytics that will help improve the treatment of patients in critical care areas such as neurologic emergencies, sepsis, cardiac arrest, and combat casualty care.
This position offers a unique opportunity in the areas of data science and analytics at the Weil Institute For Critical Care Research and Innovation within Michigan Medicine’s Department of Emergency Medicine. Research in our institute focuses on developing clinical decision support systems and a real-time analytics platform for developing and translating advanced data science into critical care.
We are looking for an ambitious, talented, and self-motivated individual with an interest in solving problems as an analytical thinker. Therefore, the candidate is expected to be a dynamic problem solver who is not afraid to “fail fast” as we look to develop the best analytics possible.
This role requires active collaboration with our Data Science team as well as with other clinical collaborators within the school and in other institutes. This collaboration will include requirements gathering to ensure we fully understand exactly what “done” looks like before we start the development of a project.
Who We Are
The Weil Institute Overview
The Weil Institute at the University of Michigan is one of the world’s first comprehensive research enterprises devoted to transforming critical care medicine by accelerating science and moving it from bench to bedside. To do this, the Weil Institute brings together integrative teams of world-class U-M scientists, clinicians, and engineers with industry partners and funding sources to develop and deploy cutting-edge solutions that elevate the care, outcomes, and quality of life of critically ill and injured patients and their families.
Responsibilities*
? Build and improve tooling to automate data pulls
? Transform ad-hoc data pulls into real-time pipelines
? Administer infrastructure to support data and applications
? Implement monitoring solutions to ensure data integrity and pipelines are operational
? Build and integrate data cataloging into pipelines to ensure data security and enable future automation
? Communicate clearly and consult with our multi-disciplinary team of scientists, developers, and clinicians
? Actively participating in discussions and decisions made by the team. We rely on each other and hold each other accountable
? Determine and document requirements
? Estimate and adjust stories and sprints
? Investigate new technologies and share with the team
Required Qualifications*
The Weil Institute Data Engineer Senior must have a bachelor’s degree in Engineering, Computer Science, Applied Mathematics, Statistics, or Data Analytics or equivalent experience with 7-10 years of increasingly complex business programming experience in a data-driven business environment.
In additional to the above requirements, candidates must also possess the following qualifications::
? Proficiency using relevant tools (Python, SQL, Docker)
? Experience working in a Unix environment
? Familiarity with ML concepts (supervised learning and deep learning)
? Knowledge of commonly used software development concepts such as unit testing, git, publish-subscribe architecture, CI/CD, and REST interfaces
? Ability to manage multiple projects and assignments with a high level of autonomy and accountability for results
? Willingness to learn and quickly adjust to new tools and systems
? Capable of converting ambiguous problem statements into concrete project requirements
? Excellent verbal and written communication skills including the ability to communicate effectively and professionally with colleagues and stakeholders. Ability to understand and explain technical concepts to non-technical stakeholders
Desired Qualifications*
? Familiarity with Kubernetes
? Familiarity with RabbitMQ
? Familiarity or experience with commonly used data science packages including numpy, pandas, scikit-learn, and tensorflow.
? Experience working with big data
? Experience developing CI/CD pipelines
? Experience working with PHI
? Epic certification for working in Clarit
Work Locations
Location
Our office is located on the University of Michigan campus in Ann Arbor, Michigan. This position is open to candidates who are seeking remote and/or hybrid location flexibility.
Background Screening
Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.
Application Deadline
Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.
U-M COVID-19 Vaccination Policy
COVID-19 vaccinations, including one booster when eligible, are required for all University of Michigan students, faculty and staff across all campuses, including Michigan Medicine. This includes those working remotely and temporary workers. More information on this new policy is available on the U-M Health Response website or the UM-Dearborn and UM-Flint websites.