Company Overview
At Amazon, we are guided by four core principles: a relentless focus on the customer over competitors, a passion for innovation, a dedication to operational excellence, and a commitment to long-term thinking. We thrive on creating technologies, developing new products, and delivering services that have a meaningful impact on people’s lives. We embrace bold ideas, move quickly, and view failure as a stepping stone to progress. While we operate with the scale of a global company, we maintain the agility and heart of a startup.
Key Responsibilities
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Manage monthly Medicare membership models and reporting processes, including data extraction, manipulation, analysis, and integration from internal data warehouses and payer/provider portals. Present variance analyses and insights to senior leadership.
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Collaborate closely with finance and business leaders to develop long-term strategies and initiatives focused on enhancing customer satisfaction.
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Work cross-functionally with teams in Business Intelligence, Data Science, and FinTech to create data-driven reports and implement driver-based forecasting tools.
Potential Project Areas
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Design and refine membership strategies to support retention and growth; maintain and update Weekly Business Review (WBR) metrics across the Senior Health business.
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Develop and maintain reconciliation models for tracking eligibility and payments.
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Contribute to FP&A (Financial Planning & Analysis) processes and related mechanisms.
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Build advanced models to assess key performance indicators (KPIs) in value-based care environments.
Basic Qualifications
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A minimum of 5 years of experience in finance, tax, or a similar analytical role.
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Bachelor’s degree in Finance, Accounting, Business, Economics, or a related quantitative field (e.g., Engineering, Math, Computer Science) and 5+ years of relevant experience; or a Master’s degree with 3+ years of experience.
Preferred Qualifications
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Advanced degree (MBA) or CPA certification.
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Proficiency in SQL and ETL processes.
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6+ years of experience identifying and resolving data inconsistencies, including root cause analysis and escalation planning.
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Demonstrated ability to solve complex business problems through the delivery of accurate, impactful financial models and recommendations that result in measurable improvements.
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Experience using large-scale data tools (e.g., SQL, MS Access, Essbase, Cognos) and enterprise financial systems (e.g., Oracle, SAP, Lawson, JD Edwards).
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Proven ability to deliver financial forecasts, budgets, variance analyses, and actionable insights.