Biological Data Scientist

University of Wisconsin–Madison; Madison (WI); Hybrid; USD 60,000 - 88,000; Full time

Benefits offered by this job

Generous vacation and holidays

Sick leave and retirement benefits

Competitive insurance and savings

Job summary

The University of Wisconsin–Madison is hiring a research-focused Biological Data Scientist to support longitudinal epidemiology work on vascular contributions to cognitive impairment and dementia.

The role involves data visualization, statistical analysis, machine learning, and data mining to address lead-research questions, along with developing reproducible workflows and data management systems for complex datasets.

Qualifications

• Experience with longitudinal cohort data and epidemiology research.
• Ability to oversee students and staff performing data analysis.
• Strong communication of methods and findings to researchers and stakeholders.

Responsibilities

• Apply data science techniques to identify data patterns and answer lead-research questions.
• Prepare datasets through cleaning, transformations, integration of sources.
• Build reproducible workflows and reports for researchers and administrators.
• Develop data management systems for merging and harmonizing complex datasets.
• Contribute to manuscripts and presentations for conferences and stakeholders.

Skills

data visualization

statistical analysis

machine learning

data mining

causal inference methods

prediction modeling

code reproducibility

Education

Master’s degree in public health/biostatistics/epidemiology

PhD in public health/biostatistics/epidemiology

Tools

R

STATA

SAS

Job description

The University of Wisconsin–Madison is hiring a research-focused Biological Data Scientist to support longitudinal epidemiology work on vascular contributions to cognitive impairment and dementia.

Responsibilities

• Apply data science techniques under guidance from data scientists, statisticians, and researchers to identify data patterns and address lead-researcher questions
• Support research questions using methods including data visualization, statistical analysis, machine learning, and data mining
• Document approaches used to address research questions
• Prepare datasets for analysis through cleaning and quality assurance, transformations, restructuring, and integration of multiple data sources
• Build reproducible workflows and reports that clearly communicate findings to researchers and/or administrators
• Organize and automate steps for data preparation and analysis
• Manage and transform multiple longitudinal cohort studies
• Support biological-driver projects for vascular contributions to cognitive impairment and dementia, including neuroimaging and blood-based biomarkers
• Develop data management systems and code for merging, harmonizing, and analyzing complex datasets
• Analyze data from surveys, laboratory assays, neuroimaging, geocoding, event data, and administrative linkages
• Optimize reproducibility, including creation of codebooks and reproducible code that can be published
• Analyze using established statistical methods, oversee students and fellow staff who conduct data analysis, and develop recommendations based on research findings
• Contribute to manuscripts and presentations for academic conferences and key stakeholders (e.g., community organizations), and support analytic plan design for future studies
• Support design of subsequent waves of data collection, including development of sampling strategies, survey instruments, and questionnaires

Requirements

• Manage, analyze, and interpret research data from complex cohort studies using R and/or STATA and/or SAS
• Work with established statistical methods, and oversee the work of students and fellow staff performing data analysis and recommendations
• Participate in independent and collaborative manuscripts and presentations at academic conferences and for key stakeholders (e.g., community organizations)
• Support design of subsequent waves of data collection, including sampling strategies, survey instruments, and questionnaires
• Working knowledge of causal inference methods and/or prediction modeling
• Ability to communicate effectively in a team setting
• Ability to write reproducible code, conduct code review, and post code publicly for reproducibility

Technologies

• R
• STATA
• SAS
• Machine learning
• Prediction modeling
• Causal inference methods

Additional Information

• Some work may be performed in-person onsite at a designated campus work location
• Some work may be performed remotely at an offsite, non-campus work location
• Applicants may be considered for titles Data Scientist I, Data Scientist II, or Data Scientist III, depending on experience and qualifications

Preferred Qualifications

• At least 1-2 years of experience working in an epidemiology or biostatistics group

Education

• Data Scientist I or II: Master’s degree in public health, biostatistics, and/or epidemiology preferred
• Data Scientist III: PhD in public health, biostatistics, and/or epidemiology preferred

Compensation

• Starting salary: $60,000 (Data Scientist I), $75,000 (Data Scientist II), $88,000 (Data Scientist III); negotiable based on experience and qualifications
• Benefits include generous vacation, holidays, sick leave, competitive insurances and savings accounts, and retirement benefits
• SMPH Faculty / Academic Staff Benefits Flyer 2026

Contact

• Caitlin Spaulding: [e-mail], 608-265-1325
• Relay Access (WTRS): 7-1-1 (see RELAY_SERVICE for further information)