Sr. Analyst - Healthcare Analytics
New
V
Valenz HealthHealthcare Analytics
United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 7+ years of experience in data analysis, including at least 3 years working with healthcare claims data
- Required Skills
- PythonSQLPandasSparkMicrosoft ExcelDatabricksPySpark
Requirements
- Bachelor's degree in Statistics, Mathematics, Engineering, Computer Science, Finance, Economics, or another quantitative field.
- 7+ years of experience in data analysis.
- At least 3 years working with healthcare claims data and complex, incomplete datasets.
- Advanced SQL skills with experience querying, transforming, validating, and optimizing large, complex datasets.
- Strong Python programming skills, including experience with Pandas, PySpark, and workflow automation.
- Experience with healthcare coding standards such as HCPCS, ICD-10, and NDC.
- Proficiency in Microsoft Excel for data validation and reporting.
- Hands-on experience with distributed data processing platforms such as Databricks and Spark.
- Experience with cloud-based data environments such as Azure, Microsoft Fabric, or Snowflake.
- Experience creating, validating, and monitoring outbound data extracts and secure file transfers (SFTP).
Responsibilities
- Analyze medical and pharmacy claims to develop and maintain data products that support pricing, quality, and compliance tools.
- Apply advanced models and queries to resolve data issues, support client inquiries, and improve internal analytics tools and workflows.
- Use tools such as SQL, Python, Spark, and Databricks to transform complex datasets into actionable insights and clear recommendations.
- Own the development, production, validation, secure delivery, and ongoing support of outbound pharmacy data extracts for multiple vendors through SFTP and other approved data exchange methods.
- Partner with Data Engineering, Web Development, and other Analytics teams to design, deploy, and sustain complex code and workflows.
- Collaborate with different departments to investigate and resolve ad hoc cases, addressing client-specific inquiries and internal requests.
- Monitor data quality and performance, identifying trends, anomalies, and opportunities for improvement.
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