Research Data Scientist – Data Quality

University of Wisconsin-Madison

. Develop, implement, and operationalize data quality capabilities within the Wisconsin Health Data Hub .

Posted 10/9/2026full-timeRemote • Wisconsin • United StatesMid-LevelSenior💰 $90,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing data quality frameworks, utilizing programming skills in Python, R, and SQL, and applying data science techniques for anomaly detection and quality monitoring. Proficient in communicating complex findings to diverse stakeholders and ensuring data governance and standardization across healthcare and research environments.

Highest-signal resume keywords

Data Quality Framework DevelopmentPython ProgrammingSQL ProficiencyData Profiling and ValidationMachine Learning Techniques

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Quality ProcessesData AnalyticsStatistical MethodsAutomated ValidationData CleansingAnomaly DetectionData StandardizationData Processing PipelinesExploratory Data AnalysisReproducible Workflows

Soft Skills

Analytical SkillsProblem-SolvingCommunication Skills

Tools & Technologies

Azure SynapseMS FabricADFCloud Environments

Certifications & Qualifications

PhD or Terminal Degree in Data ScienceComputer ScienceStatisticsBiostatisticsBiomedical InformaticsInformation Systems

Industry Keywords

Healthcare Data ModelsResearch Data ManagementClinical DataBiomedical DataData Governance

Tech Stack

Tools & technologies

AzureCloudPythonSQL

About the role

Key responsibilities & impact

Develop, implement, and operationalize data quality capabilities within the Wisconsin Health Data Hub
Design and maintain scalable data quality frameworks for clinical, biomedical, and research datasets
Perform data profiling and exploratory analysis to identify anomalies, missingness, inconsistencies, and quality issues
Develop statistical and computational methods, rules, thresholds, metrics, and validation criteria
Apply data science and machine learning techniques for anomaly detection and quality monitoring
Build automated validation and quality-control processes, reusable components, scripts, services, and APIs
Integrate quality checks and monitoring into cloud-based data pipelines and analytics environments
Collaborate with data engineers, data scientists, informaticians, architects, security specialists, researchers, and stakeholders
Improve data standardization, normalization, harmonization, interoperability, provenance, metadata, and documentation
Evaluate research readiness and limitations of datasets for analysis, modeling, AI, and research applications
Establish data quality governance policies, standards, definitions, procedures, and accountability frameworks
Communicate findings and recommendations to technical and non-technical stakeholders
Develop reproducible workflows, reports, dashboards, and data quality tools
Contribute to technology transfer and sustainable adoption across academic, healthcare, and industry research environments

Requirements

What you’ll need

3 to 5 years’ professional experience in data science, research data management, data quality, data analytics, or a related technical field
Strong programming experience in Python, R, and SQL
Experience developing and implementing data quality processes, including profiling, validation, cleansing, standardization, anomaly detection, and quality monitoring
Experience with large-scale datasets and data processing pipelines across multiple structured and/or unstructured data sources
Ability to develop automated data quality rules, metrics, validation frameworks, and monitoring processes
Strong analytical and problem-solving skills
Ability to communicate complex data quality findings to technical and non-technical stakeholders
Must reside in Wisconsin or relocate within a reasonable timeframe
Continuous eligibility to work in the United States without employer sponsorship; university sponsorship, TN visas, and J-1 waivers are unavailable
Cover letter and resume required
PhD or terminal degree preferred in Data Science, Computer Science, Statistics, Biostatistics, Biomedical Informatics, Information Systems, or related technical field
Preferred: clinical, healthcare, or research data experience; healthcare data models and standards; cloud environments; Azure Synapse, MS Fabric, ADF; EHR data; reproducible data science workflows

Benefits

Comp & perks

Generous vacation, holidays, and sick leave
Competitive insurances and savings accounts
Retirement benefits