Data Analyst

Summary

Post Acute Analytics is a healthcare technology company transforming post-acute care through its Anna platform, which connects providers, payers, and caregivers with clinical intelligence and connected technology. The Data Analyst will support Operations and Client Success by analyzing client performance, investigating trends and root causes, identifying network opportunities, and building reusable analytical assets and decision-ready reporting.

Responsibilities

• Analyze how each client is performing against contractual goals, KPIs, and operational benchmarks on the Anna™ platform
• Build and maintain reporting views that give Client Success leaders and account owners a clear, current picture of book-of-business health
• Surface leading indicators of client risk or opportunity before they become escalations
• Support QBR, executive review, and internal client success planning cycles with reliable, decision-ready analytics
• Investigate the drivers behind client performance trends — utilization shifts, workflow changes, provider network dynamics, seasonality, product usage patterns
• Move from "what happened" to "why" using cohort analysis, comparative benchmarking, and appropriate statistical methods
• Translate findings into clear narratives — charts, memos, briefings — that operational leaders and clients can act on without a translator
• Support broader Operations with data-driven insight into provider network coverage, capacity, and integration health across the SNF, home health, and broader post-acute footprint
• Identify macro-level opportunities (market gaps, network expansion priorities, integration friction patterns) and micro-level opportunities (specific facility outliers, workflow bottlenecks, data quality issues)
• Work with large, varied, and sometimes messy datasets — Anna platform data, claims, EHR/EMR extracts, client-provided files — and bring rigor to how they're structured, joined, validated, and interpreted
• Build reusable data assets (queries, models, dashboards, notebooks) that scale beyond a single analysis and outlast a single request
• Partner with the VP, Analytics on analytical standards, methods, documentation, and reusable frameworks; contribute back to the broader analytics function

Skills

• 3–5 years of hands-on data analyst experience with proven fluency working across large and varied datasets
• Strong background / experience with SQL. Writing complex queries against large relational datasets comfortably, including joins, window functions, CTEs, and performance-aware patterns
• Working proficiency in Python or R for analysis (ex. Pandas, Jupyter notebooks, basic statistical methods)
• Data visualization capability in Tableau, Power BI, Looker, or comparable. Building views to inform executive decision-making
• Solid grasp of analytical fundamentals: cohorting, benchmarking, distributions, basic statistical inference;  enough judgment to know when to reach for what
• Advanced Excel for ad hoc work and executive-facing summaries
• Ability to translate messy operational questions into clean analytical problems, and analytical output into clear narratives non-analysts can act on
• Bachelor's degree in a quantitative or analytical discipline (data science, statistics, economics, mathematics, engineering, public health, informatics, or comparable)
• Experience with healthcare data — claims, EHR/EMR data, HL7/FHIR standards, or utilization and case management data
• Familiarity with post-acute care, managed care, Medicare Advantage, or value-based care contexts
• Prior experience embedded within an operational or client-facing team, not only centralized analytics or BI
• Working familiarity with clinical outcomes concepts — readmissions, LOS, ED utilization, total cost of care

Qualifications

Must Haves

• 3–5 years of hands-on data analyst experience with proven fluency working across large and varied datasets
• Strong background / experience with SQL. Writing complex queries against large relational datasets comfortably, including joins, window functions, CTEs, and performance-aware patterns
• Working proficiency in Python or R for analysis (ex. Pandas, Jupyter notebooks, basic statistical methods)
• Data visualization capability in Tableau, Power BI, Looker, or comparable. Building views to inform executive decision-making
• Solid grasp of analytical fundamentals: cohorting, benchmarking, distributions, basic statistical inference;  enough judgment to know when to reach for what
• Advanced Excel for ad hoc work and executive-facing summaries
• Ability to translate messy operational questions into clean analytical problems, and analytical output into clear narratives non-analysts can act on
• Bachelor's degree in a quantitative or analytical discipline (data science, statistics, economics, mathematics, engineering, public health, informatics, or comparable)

Nice to Haves

• Experience with healthcare data — claims, EHR/EMR data, HL7/FHIR standards, or utilization and case management data
• Familiarity with post-acute care, managed care, Medicare Advantage, or value-based care contexts
• Prior experience embedded within an operational or client-facing team, not only centralized analytics or BI
• Working familiarity with clinical outcomes concepts — readmissions, LOS, ED utilization, total cost of care

Benefits

• Annual performance bonus
• Equity participation commensurate with experience
• Comprehensive medical, dental, and vision coverage, effective the 1st of the month after start date
• 401(k) with employer match
• Remote or hybrid work
• Flexible PTO
• 10 paid holidays
• Frequent team offsites
• Matrixed mentorship from the VP, Analytics
• Direct exposure to operational leadership
• Learning & development budget
• Real influence on how PAA uses data