Principal Data Analyst - Product Optimization, Healthcare Revenue Cycle

FinThrive is advancing the healthcare economy through healthcare revenue management solutions. The Principal Data Analyst will transform complex healthcare revenue cycle data into evidence-based product decisions for the Insurance Discover product, using SQL, Databricks, statistical analysis, and AI-assisted analytics. The role partners with cross-functional stakeholders to identify product and data quality issues, measure performance, and recommend improvements that enhance customer outcomes and recovered revenue.

Responsibilities:

• Develop and maintain deep subject matter expertise in Insurance Discover, including product lifecycle, customer workflows, eligibility / coverage discovery logic, data ingestion, matching behavior, operational processes, and the value chain required to deliver customer outcomes
• Analyze large, complex healthcare revenue cycle datasets to identify trends, gaps, anomalies, failure patterns, data quality issues, and opportunities to improve product accuracy, performance, scalability, and customer impact
• Use advanced SQL and big-data tooling such as Databricks to query, structure, profile, and interpret high-volume datasets across multiple sources and operational workflows
• Apply descriptive, diagnostic, and basic statistical techniques to assess product performance, validate hypotheses, measure impact, and distinguish signal from noise in complex data environments
• Leverage AI-assisted analytics, automation, and emerging AI capabilities to accelerate pattern detection, anomaly identification, root-cause exploration, documentation, and insight generation while maintaining strong quality controls
• Build metrics, dashboards, scorecards, and analytical frameworks that measure the effectiveness of product enhancements, operational optimizations, and customer-facing outcomes
• Translate technical analysis into clear recommendations, business cases, decision support, and executive-ready narratives for Product, Technology, Operations, Finance, Sales, and leadership stakeholders
• Partner with cross-functional teams to prioritize improvements, define success measures, support implementation, and monitor whether changes deliver the intended business and customer outcomes
• Support high-impact initiatives related to data integrity, coverage discovery performance, integration workflows, reporting accuracy, process optimization, and product stabilization / enhancement efforts
• Become a trusted analytical partner who can challenge assumptions, frame ambiguous problems, and bring structure to complex data questions in a fast-paced, matrixed environment

Requirements:

• Bachelor's degree in Statistics, Data Science, Information Systems, Computer Science, Mathematics, Economics, Engineering, Healthcare Informatics, or another quantitative / technical field; advanced degree preferred but not required
• 6+ years of experience in data analytics, product analytics, business analytics, healthcare analytics, revenue cycle analytics, or a related analytical role
• Healthcare revenue cycle experience, ideally with exposure to eligibility, coverage discovery, claims, denials, patient access, payer data, provider workflows, or healthcare data exchange
• Advanced SQL skills, including complex joins, CTEs, window functions, aggregation logic, data validation, performance-aware querying, and analysis across large, messy datasets
• Hands-on experience with big-data environments or cloud data platforms such as Databricks, Snowflake, Azure Data Lake, Synapse, Spark, or comparable tools
• Strong statistical and analytical foundation, with the ability to apply practical methods such as cohort analysis, segmentation, variance analysis, trend analysis, outlier detection, correlation, sampling, confidence-based reasoning, or experiment / impact measurement
• Technical fluency with data pipelines, data models, data quality concepts, APIs / data exchange patterns, and the practical realities of working with operational healthcare data
• Experience using AI-enabled tools or analytics approaches to improve productivity, identify patterns, summarize findings, document analysis, or support decision-making; must be comfortable experimenting with responsible AI use cases
• Proficiency in data visualization and storytelling using Tableau, Power BI, SSRS, Excel, or similar tools, with the ability to create leadership-ready insights rather than simply reporting numbers
• Ability to communicate clearly with both technical and non-technical stakeholders, including translating complex findings into concise recommendations, risks, tradeoffs, and next steps
• Strong problem-solving, critical thinking, prioritization, and project management skills; ability to drive multiple initiatives with minimal supervision in a collaborative, matrixed environment
• Experience supporting product optimization, product operations, product performance management, or data-driven product strategy in a healthcare technology environment
• Working knowledge of payer / provider data, EHR or practice management workflows, eligibility transactions, insurance discovery, coverage verification, or revenue recovery processes
• Practical Python or PySpark experience for data manipulation, statistical exploration, automation, or repeatable analytical workflows
• Experience designing analytical QA checks, data reconciliation logic, exception reporting, or repeatable monitoring frameworks for operational data products
• Familiarity with model-assisted analysis, machine learning concepts, predictive analytics, or experimentation frameworks; ability to partner with data science or engineering teams when deeper modeling is required
• Comfort operating in ambiguous problem spaces where the first task is to define the problem, locate the data, validate assumptions, and create a structured path to action