Senior Data Analyst; Remote

Resp & Qualifications

PURPOSE: The Senior Data Analyst is responsible for ensuring the accuracy, completeness, and regulatory compliance of data supporting Risk Adjustment programs, CMS submissions, and associated healthcare analytics. This role leads the design and execution of automated testing frameworks, data certification processes, reconciliations, and balance-and-control activities used to validate enrollment, claims, diagnosis, provider, and clinical data across the end-to-end Risk Adjustment ecosystem.

The Senior Data Analyst serves as a subject matter expert for Risk Adjustment data quality, partnering with business, operations, compliance, and engineering teams to perform root cause analysis, resolve complex data defects, strengthen operational controls, and ensure trusted data supports risk score accuracy, financial integrity, audit readiness, and regulatory reporting ESSENTIAL FUNCTIONS:

• Engages in data exploration using various programming languages (reading and writing code), requiring advanced knowledge of multiple database structures.
• Collect, analyze, and interpret data to glean insights, and develop business appropriate recommendations.
• Research and analyze data flow across complex data ecosystem including operational and analytical data platforms.
• Serve as an expert resource supporting data questions and issues from stakeholders and driving to resolution.
• Lead in the design, development, validation and delivery of data to provide insight into business decisions.
• Manage the collection of business and technical requirements from Stakeholders to deliver data driven solutions. Produces technical documentation that is consistent with professional standards.
• Be a resource and mentor to junior level staff

SUPERVISORY RESPONSIBILITY Position does not have direct reports but is expected to assist in guiding and mentoring less experienced staff. May lead a team of matrixed resources.
QUALIFICATIONS:
Education Level: Bachelor's Degree in Data Science, Mathematics, Computer Science, Statistics, Business or related field OR in lieu of a Bachelor's degree, an additional 4 years of relevant work experience is required in addition to the required work experience.
Experience: 5 years experience in an analytical/quantitative role.
Preferred Qualifications
:

• Experience in Healthcare Industry.
• Hands on experience with Big Data/No
  
  SQL Platforms with experience delivering production projects at scale.

Knowledge,

Skills and Abilities

(KSAs)

• Expert knowledge of healthcare payer data domains, including claims, enrollment, provider, diagnosis, procedure, pharmacy, and clinical data, and their impact on Risk Adjustment reporting, analytics, and financial performance.
• Expert knowledge of Risk Adjustment business processes, including diagnosis capture, HCC models, coding validation, chart review programs, risk score generation, prospective and retrospective workflows, and associated data dependencies.
• Expert ability to design, implement, and maintain automated data testing, certification, validation, reconciliation, and monitoring frameworks that ensure data accuracy and regulatory compliance.
• Expert understanding of balance-and-control methodologies, data reconciliations, exception management, and production certification processes supporting critical healthcare reporting and submissions.
• Expert knowledge of data quality management principles, including completeness, accuracy, validity, consistency, timeliness, traceability, and data control frameworks.
• Advanced knowledge of regulatory reporting and submission processes supporting Risk Adjustment operations, audit readiness, and healthcare compliance requirements.
• Expert proficiency in SQL and advanced data analysis techniques used to perform root cause analysis, validate business rules, investigate anomalies, quantify impacts, and resolve complex data defects.
• Strong knowledge of cloud data platforms and analytical environments, including Snowflake, Microsoft Fabric, Azure Data Factory (ADF), and related healthcare data ecosystems.
• Expert understanding of end-to-end data lineage, source-to-target mappings, transformation logic, business rules, and operational workflows supporting Risk Adjustment data processing.
• Expert ability to lead defect triage, issue management, remediation validation, and post-production monitoring activities across multiple business and technology teams.
• Advanced knowledge of metadata management, data governance, auditability, lineage, and control frameworks supporting trusted and compliant data assets.
• Advanced knowledge of Agile delivery methodologies, testing practices, release validation, and production readiness processes.
• Expert analytical and problem-solving skills with the ability to evaluate complex healthcare data scenarios, identify risks, determine root causes, and recommend sustainable corrective actions.
• Advanced written and verbal communication skills with the ability to communicate testing results, defect impacts, data quality risks, and remediation…