Job Description

Job Summary:
Are you passionate about improving patient health outcomes, optimizing healthcare processes, and advancing science? Join our dynamic Informatics and Information Technology team at the University of Wisconsin School of Medicine and Public Health in Madison, Wisconsin. We are committed to revolutionizing healthcare through implementation of advanced data science approaches, conducting cutting-edge data-centric research, and generating real-world evidence to improve patient health outcomes at UW Health and beyond. As a Data Scientist, the incumbent will use real world data including Electronic Health Record (EHR) data to develop and implement advanced computational algorithms and support conduct of groundbreaking data-driven research.

On a day-to-day basis, the incumbent could expect to engage in the following activities:
- Data Collection and Preprocessing: preprocess, and validate EHR data, ensuring data quality and reliability; and transform raw data into standard data models (OMOP, mCODE, i2b2 etc.).
- Algorithm Development and Optimization: develop and optimize advanced computational algorithms using Artificial Intelligence (AI), Machine Learning (ML), regression, and rules-based models; apply AI/ML techniques to analyze EHR data, to uncover hidden biological and health patterns and gain meaningful insights; evaluate, validate, and implement AI/ML models, regression, and rules-based algorithms on UW Health EHR data; and ensure the reliability and accuracy of algorithms for production environments.
- Feature Engineering and Selection: identify key features of EHR data to enhance model performance; and apply domain-specific knowledge to identify meaningful features for predictive modeling.
- Predictive Modeling and Insights: build predictive models to forecast disease risk and progression, health outcomes, and treatment effectiveness; and gain actionable insights from model outputs and communicate findings to research community.
- Natural Language Processing (NLP): apply NLP techniques to extract insights from clinical notes, reports, and unstructured text data; and develop models for sentiment analysis, entity recognition, and information extraction.
- Integration and Optimization: integrate research outcomes with existing AI systems and databases to advance technological capabilities; and continuously optimize, troubleshoot, and debug AI algorithms based on research outcomes and evolving business needs.
- Stay Ahead of Emerging Technologies: keep abreast of emerging trends and advancements in AI research to propose innovative solutions to healthcare challenges.
- Collaboration and Communication: work closely with cross-functional teams, including clinicians, data scientists, data engineers, and product managers; and present research findings and recommendations in a clear and actionable manner.
- Ethical Considerations: ensure compliance with privacy regulations (e.g., NIST, HIPAA) when working with healthcare data; and address bias and fairness issues in AI models when dealing with sensitive health data.

Responsibilities:
Contributes to a research agenda set by a lead researcher by preparing data sets, analyzing them using data science techniques, and presenting the results. Plays a leadership role and may lead a team and/or personnel.
10% Prepares data sets for analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources
15% Identifies and implements or guides others in implementing appropriate data science techniques to find data patterns and answer research questions chosen by the lead researcher including data visualization, statistical analysis, machine learning, and data mining
10% Organizes and automates project steps for data preparation and analysis
10% Composes and assembles reproducible workflows and reports to clearly articulate patterns to researchers and/or administrators
15% Documents approaches to address research questions and contributes to the establishment of reproducible research methodologies and analysis workflows
15% Serves as an institutional subject matter expert and liaison to key internal and external stakeholders regarding data science best practices and methodologies and represents the interests of data science
5% May supervise the data-to-day activities of staff and resolves routine personnel issues
20% Develops and optimizes advanced computational algorithms using Artificial Intelligence (AI), Machine Learning (ML), regression, and rules-based models
Institutional Statement on Diversity:
Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals.

The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background - people who as students, faculty, and staff serve Wisconsin and the world.