Senior Data Analyst

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.

Data Quality & Analysis

• Perform detailed data quality audits to detect, troubleshoot, and resolve issues impacting accuracy and completeness.
• Conduct in-depth analysis of data quality and integrity to identify and resolve issues.
• Create and execute SQL queries to validate data transformations and support data analysis efforts.
• Analyze and troubleshoot ETL processes and data architectures for performance and quality.
• Develop, generate, and maintain client program reports, ensuring accuracy, timeliness, and alignment with client expectations and business objectives.
• Perform detailed data analysis and reconciliation activities to ensure program integrity, including validating outputs against source data and expected results.
• Track and analyze program performance over time, identifying variances, root causes, and trends to ensure accuracy and consistency of results.
• Reconcile data across multiple sources (e.g., claims, eligibility, and reporting outputs) to ensure alignment and completeness.
• Partner with internal teams to investigate discrepancies, implement corrections, and ensure accurate downstream reporting and client deliverables.
• Develop, generate, and maintain recurring and ad hoc reports for both internal stakeholders and external clients, ensuring accuracy, clarity, and timeliness.

Collaboration & Communication

• Collaborate cross-functionally with business stakeholders to translate data needs into technical specifications.
• Support onboarding new client data feeds, ensuring smooth integration with minimal disruption.
• Partner with data engineers to build and scale data pipelines, improving performance and reliability.
• Serve as a subject matter expert for healthcare claims data—advising on risk, trends, and business impact.
• Work closely with data scientists to enable advanced analytics, ML models, and reporting use cases.
• Excellent written and verbal communication skills, especially when explaining technical concepts to non-technical stakeholders.
• Coordinate and support cross-functional project activities, including tracking deliverables, timelines, and dependencies to ensure successful project execution.
• Work directly with internal teams and client stakeholders to define reporting requirements, KPIs, and success metrics.
• Translate analytical findings into clear, actionable insights through dashboards, reports, and presentations tailored to both technical and non-technical audiences.
• Ensure consistency and standardization of reporting outputs across programs and clients.

Continuous Improvement

• Troubleshoot ETL workflows and performance issues, driving continuous improvement in data architecture.
• Create comprehensive documentation of data mapping, transformation, and validation processes.
• Identify opportunities to improve reporting processes, streamline workflows, and enhance project coordination efficiency.
• Continuously evaluate and enhance reporting frameworks, dashboards, and delivery processes to improve efficiency, scalability, and client value.
• Collaborate with data engineering teams to evaluate and implement new data pipelines, mining engines, and other technologies to enhance data analysis capabilities.

Data Transformation & Mapping

• Design and maintain robust data transformations and mappings to convert raw medical claims and eligibility data into standardized canonical models.
• Develop complex data mappings and structures to support advanced analytics, reporting, and decision-making.
• Document data transformation logic and lineage to ensure transparency and reusability.

What experience you bring (Role Requirements):

• Bachelor’s degree in business, Computer Science, Health Informatics, or a related field.
• 3+ years of experience as a data analyst or business analyst working with large datasets.
• 2+ years of hands-on experience with healthcare claims data (e.g., 837 EDI, medical billing, encounter data).
• Experience within a healthcare-related field working with very large data sets of medical and pharmacy claims.
• Advanced proficiency in SQL and familiarity working with Spark, Snowflake, DPE or similar big data frameworks.
• Solid understanding of data modeling concepts and best practices for analytics.
• Proven problem-solving skills and attention to detail in complex data environments.
• Strong organizational skills and ability to manage multiple concurrent initiatives.
• Excellent communication, time-management, and task prioritization skills.
• Ability to build and maintain strong working relationships across the organization.
• Self-starter with a strong sense of ownership and accountability.