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University of Wisconsin-Madison
University of Wisconsin-Madison
ŠvietimasVyriausybė
University of Wisconsin-Madison yra valstybinis mokslinių tyrimų universitetas Madisone, Viskonsino valstijoje, ir pagrindinis Viskonsino universiteto sistemos miestelis. Jo akademinė ir mokslinių tyrimų bendruomenė apima humanitarinius mokslus, gamtos mokslus ir taikomąsias disciplinas, o moksliniams tyrimams kasmet skiriama daugiau nei 1 mlrd. JAV dolerių. Universitetas derina bakalauro ir magistrantūros studijas su darbuomenės veikla, miestelio ištekliais ir sportu, vadovaudamasis Viskonsino idėja, kurios pagrindą sudaro dėmesys viešajai tarnystei. Jo veikloje taip pat pabrėžiama įvairovė, įtraukusis meistriškumas ir bendradarbiavimas su platesne bendruomene.
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Research Data Scientist, Data Quality — University of Wisconsin-Madison

Lead data-quality engineering and analysis for UW–Madison’s Wisconsin Health Data Hub. Strengthen clinical and biomedical datasets for research, analytics, and AI applications.

USJungtinės ValstijosWIViskonsinas
90 000 $ / metai
NuotolinisVisas etatasVidutinis lygisVyresnysis specialistasPrivaloma Kalba: anglųDuomenų mokslininkas
AzureDebesijaPythonSQL

Aprašymas

  • Build and operationalize data-quality capabilities for the Wisconsin Health Data Hub
  • Create and maintain scalable quality frameworks for clinical, biomedical, and research datasets
  • Profile data and conduct exploratory analyses to uncover anomalies, missing values, inconsistencies, and other quality concerns
  • Define statistical and computational methods, rules, thresholds, metrics, and validation standards
  • Use data science and machine learning methods for anomaly detection and ongoing quality monitoring
  • Develop automated validation and quality-control workflows, reusable components, scripts, services, and APIs
  • Embed quality checks and monitoring within cloud data pipelines and analytics environments
  • Partner with engineers, data scientists, informaticians, architects, security specialists, researchers, and other stakeholders
  • Advance data standardization, normalization, harmonization, interoperability, provenance, metadata, and documentation
  • Assess dataset readiness and constraints for analysis, modeling, artificial intelligence, and research use
  • Create data-quality governance policies, standards, definitions, procedures, and accountability models
  • Present findings and recommendations clearly to both technical and non-technical audiences
  • Produce reproducible workflows, reports, dashboards, and data-quality tools
  • Support technology transfer and durable adoption across academic, healthcare, and industry research settings

Reikalavimai

  • At least 3–5 years of professional experience in data science, research data management, data quality, data analytics, or a related technical discipline
  • Advanced programming experience with Python, R, and SQL
  • Hands-on experience creating and applying data-quality processes such as profiling, validation, cleansing, standardization, anomaly detection, and monitoring
  • Experience handling large datasets and processing pipelines spanning multiple structured and/or unstructured sources
  • Ability to automate data-quality rules, metrics, validation frameworks, and monitoring workflows
  • Strong analytical judgment and problem-solving ability
  • Ability to explain complex data-quality findings to technical and non-technical stakeholders
  • Current residence in Wisconsin or willingness to relocate within a reasonable timeframe
  • Ongoing authorization to work in the United States without employer sponsorship; university sponsorship, TN visas, and J-1 waivers are unavailable
  • Application must include a cover letter and resume
  • PhD or another terminal degree in Data Science, Computer Science, Statistics, Biostatistics, Biomedical Informatics, Information Systems, or a related technical field is preferred
  • Preferred background includes clinical, healthcare, or research data; healthcare data models and standards; cloud platforms; Azure Synapse, Microsoft Fabric, or ADF; EHR data; and reproducible data-science workflows

Privalumai

  • Substantial vacation, holiday, and sick leave allowances
  • Competitive insurance coverage and savings-account options
  • Retirement benefits

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