Senior Health Data Operations Analyst
New
V
Veeva SystemsHealthcare data
Source API remote eligibility restrictions: United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 4+ years of experience analyzing record-level prescription and medical claims datasets; 4+ years of experience in health data quality analysis, data profiling, and data governance principles.
- Required Skills
- SQLMicrosoft Excel
Requirements
- Have 4+ years of experience analyzing record-level prescription and medical claims datasets.
- Have 4+ years of experience in health data quality analysis, data profiling, and data governance principles.
- Demonstrate advanced SQL proficiency, including querying, manipulating, and aggregating large-scale relational databases.
- Have working knowledge of healthcare code sets and standards, including NDC, ICD-10, CPT/HCPCS, LOINC, and payer/plan reference data.
- Have experience analyzing, visualizing, and presenting data quality findings using Excel, BI tools such as Tableau, Power BI, or Sigma, or interactive dashboards.
- Hold a bachelor’s degree in a STEM, quantitative, or healthcare informatics field, or have equivalent practical experience.
- Python experience is a plus.
- Experience with Sigma and the life science industry is a plus.
Responsibilities
- Maintain and expand the Terminology Reference Library, managing reference datasets for prescription and medical claims.
- Evaluate potential data sources through data querying, field mapping, and structural analysis, and integrate suitable sources into core schemas.
- Perform exploratory data analysis to identify discrepancies and missing values, deduplicate data, and ensure completeness, accuracy, and timeliness.
- Investigate data anomalies in the Veeva Compass product suite and test planned and unplanned data changes for downstream customer impact.
- Develop interactive dashboards to track data quality metrics.
- Contribute to technical documentation, validation reports, and team process improvements.
- Partner with Data Scientists, Product Managers, and Developers to communicate data quality nuances, uncover root causes, and build data pipelines.
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