The University of Wisconsin School of Medicine and Public Health is looking to revolutionize healthcare through the implementation of advanced data science approaches, conducting cutting-edge data-centric research, and generating real-world evidence to improve patient health outcomes in WI. They need a Data Scientist to use clinical, omics, and imaging data to develop and implement advanced computational algorithms and support groundbreaking data-driven research.
Requirements
- Analysis of large-scale human sample-based omics data (genomics/proteomics/metabolomics) and strong knowledge of bioinformatics tools and databases.
- Analysis of EHR data
- Analysis of Ophthalmic imaging data
- Proficiency in programming languages such as Python, R, and SQL.
- Experience with statistical analysis and machine learning techniques.
- Excellent problem-solving skills and attention to detail.
- Develops and optimizes advanced computational algorithms using Artificial Intelligence (AI), Machine Learning (ML), regression, and rules-based models.
Responsibilities
- Develop and implement informatics pipelines for clinical, omics or imaging data processing, integration, and visualization.
- Analyze and interpret large-scale omics or imaging datasets using advanced computational/bioinformatics methods.
- Apply statistical and machine learning techniques to identify patterns and insights from complex clinical and biological data.
- Develop/validate advanced computational algorithms using Artificial Intelligence (AI), Machine Learning (ML), regression, and rules-based models.
- 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.
- 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.
- 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
Other
- 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.
- Work closely with data governance and security to 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.
- Keep abreast of emerging trends and advancements in AI research to propose innovative solutions to healthcare challenges.
- Strong communication skills and ability to work collaboratively in a team environment.
- Terminal Degree preferred, MD or PhD with a focus in Computer Science, Data Science, Clinical Informatics, Bioinformatics Epidemiology, Biostatistics, Ophthalmology or related disciplines preferred
