Research Data Scientist

About Us: The UW School of Medicine and Public Health (SMPH) is a leader in research and innovation, dedicated to improving patient outcomes through advanced data science and analytics. We are seeking experienced Research Data Scientists for the Data Science to Promote Precision Medicine initiative, and drive transformative data science projects to enhance healthcare and research at SMPH.

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 in WI. As a Data Scientist, the incumbent will use clinical, omics and imaging 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 in supporting researchers:
- 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.
- 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.

• 15% Prepares data sets for analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources
• 15% Independently identifies and implements 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
• 15% Organizes and automates project steps for data preparation and analysis
• 15% Composes and assembles reproducible workflows and reports to clearly articulate patterns to researchers and/or administrators
• 20% Documents approaches to address research questions and contributes to the establishment of reproducible research methodologies and analysis workflows
• 20% Develops and optimizes advanced computational algorithms using Artificial Intelligence (AI), Machine Learning (ML), regression, and rules-based models

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.

For more information on diversity and inclusion on campus, please visit: Diversity and Inclusion

Preferred
Master's Degree
Preferred in Computer Science, Data Science, Clinical Informatics, Bioinformatics Epidemiology, Biostatistics, Ophthalmology or related disciplines.

Required:
- At least three years of experience in any of the following:
- 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.
- Strong communication skills and ability to work collaboratively in a team environment.

Preferred:
- Experience working in academic institutions.

Full Time: 100%

This position may require some work to be performed in-person, onsite, at a designated campus work location. Some work may be performed remotely, at an offsite, non-campus work location.

Ongoing/Renewable

Minimum $80,000 ANNUAL (12 months)
Depending on Qualifications
The starting salary for the position is $80,000 but is negotiable based on experience and qualifications.

Employees in this position can expect to receive benefits such as generous vacation, holidays, and sick leave; competitive insurances and savings accounts; retirement benefits. Benefits information can be found at (https://hr.wisc.edu/benefits/).

SMPH Academic Staff Benefits flyer: (https://uwmadison.box.com/s/r50myohfvfd15bqltljn0g4laubuz7t0)

One vacancy is part of the Wisconsin Research, Innovation and Scholarly Excellence (RISE) Initiative. Through accelerated and strategic faculty hiring, research infrastructure enhancement, interdisciplinary collaboration, and increased student and educational opportunities, RISE addresses complex societal challenges of importance to the state, nation and world. Building on UW-Madison's strengths, RISE expands the University's successful track record of connecting with communities and industry on collaborative solutions.

Over the next three academic years, UW-Madison will substantially increase current research computing personnel and hardware infrastructure. Candidates hired through RISE will join a community of scholars working across disciplines, schools and colleges on research, teaching and outreach endeavors. The RISE community, and extended campus community, will engage regularly in venues such as seminar series and colloquia to share ongoing projects and identify opportunities to work together. The University will support the community, facilitating access to research infrastructure, and funding to support broad and rich collaboration.

Further information regarding RISE can be found at: https://rise.wisc.edu/

University sponsorship is not available for this position, including transfers of sponsorship and TN visas. The selected applicant will be responsible for ensuring their continuous eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of appointment. This position is an ongoing position that will require continuous work eligibility. If you are selected for this position you must provide proof of work authorization and eligibility to work.

To apply for this position, please click on the "Apply Now" button. You will be asked to upload a current resume/CV and a cover letter briefly describing your qualifications and experience.

Aisha Liebenow
liebenow@wisc.edu
608-262-5743
Relay Access (WTRS): 7-1-1. See RELAY_SERVICE for further information.

Data Scientist II(RE021)

A53-MEDICAL SCHOOL/Informatics and IT

Academic Staff-Renewable

313995-AS