Healthcare Data Scientist – ML AI Stats
Job in
Linthicum, Anne Arundel County, Maryland, USA
Listed on 2026-03-01
Listing for:
NLP PEOPLE
Full Time
position Listed on 2026-03-01
Job specializations:
-
IT/Tech
Data Scientist, Machine Learning/ ML Engineer, AI Engineer, Data Analyst
Job Description & How to Apply Below
The Healthcare Data Scientist – Machine Learning/AI, Statistics, Operations Research position will join our Advanced Data Science group at the University of Maryland Medical System (UMMS) in support of its strategic priority to become a data‑driven and outcomes‑oriented organization. The successful candidate will have experience with Machine Learning/AI, Statistics and Operations Research and a passion for working with healthcare data. Previous experience with various computational approaches along with an ability to demonstrate a portfolio of relevant prior projects is essential.
This position will report to the Director for Advanced Data Science & Consulting Services.
- Support analytic efforts designed around the organization’s strategic priorities and clinical/business problems.
- Develop predictive (machine learning and deep learning) and prescriptive (mathematical optimization and simulation) analytic models in support of the organization’s clinical, operations and business initiatives and priorities.
- Deploy solutions so that they provide actionable insights to the organization and are embedded or integrated with application systems.
- Work with the analytics team and clinical/business stakeholders to develop pilots so that they may be tested and validated in pilot/incubator settings.
- Perform statistical analysis to evaluate primary and secondary objectives from such pilots.
- Support development of strategic, tactical and operational presentations that summarize the results of predictive and prescriptive analytics projects in support of robust strategies for the organization.
- Build and extend our analytics portfolio supported by robust documentation.
- Work in a team to drive disruptive innovation, which may translate into improved quality of care, clinical outcomes, reduced costs, temporal efficiencies and process improvements.
- Assist leadership with strategies for scaling successful projects across the organization, and enhance the analytics applications based on feedback from end‑users and clinical/business consumers.
- Assist leadership with dissemination of success stories (and failures) in an effort to increase analytics literacy and adoption across the organization.
- Work with autonomy to find solutions to complex problems using open source tools and in‑house development.
- Stay abreast of state‑of‑the‑art literature in the fields of machine learning/AI, operations research, statistical modeling, statistical process control and mathematical optimization.
- PhD degree in applied mathematics, data science, physics, computer science, engineering, statistics, economics or a related field required; comparable work experience may be substituted for the PhD degree.
- Preferred 3+ years of industry experience in the following:
- Machine Learning/AI, Statistics or Operations Research.
- Programming with SQL, Python and R.
- Practical experience with machine learning/AI problems, or formulating and solving mathematical (deterministic and stochastic) optimization problems and simulation, or performing advanced statistical analysis.
- Developing and applying computational algorithms and statistical methods to healthcare data (including, but not limited to data from electronic medical record, financial management, human resources, quality and supply chain).
- Developing and deploying healthcare‑relevant predictive and prescriptive models.
- Combining analytic methods and advanced data visualizations.
- Text mining and Natural Language Processing (NLP) is preferred.
- Senior (5+ years of experience)
Skills and Abilities
- Develop (from scratch) machine learning and/or deep learning approaches and algorithms to solve clinical and business (including operations, supply chain, human resources, finance) problems.
- Formulate and solve complex mathematical optimization problems using exact and heuristic approaches.
- Perform independent/unsupervised exploratory data analysis and advanced statistical analysis (e.g., regression analysis, cluster analysis, factor analysis, ANOVA).
- Design and prototype new application functionality for our products.
- Work with “real world” data including…
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