Data Analyst

• 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

Requirements

• 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)

Preferred

• 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

Compensation — Competitive base salary, annual performance bonus, and equity participation commensurate with experience. Benefits — Comprehensive medical, dental, and vision. 401(k) with employer match. Effective the 1st of the month after start date.

Flexibility — Remote or hybrid. Flexible PTO. 10 paid holidays. Frequent team offsites.

Growth — Matrixed mentorship from the VP, Analytics, direct exposure to operational leadership, a learning & development budget, and real influence on how PAA uses data.