• Design and develop analytics models and tools to optimize transportation cost, speed, and network performance • Own and enhance key tools including carrier dashboards, routing optimizers, chargeback systems, and cost benchmarking engines • Deliver predictive and real-time reporting on key KPIs such as transit time, on-time delivery, and freight spend • Provide fast, ad hoc decision support with clear focus on business drivers and actionable insights • Collaborate cross-functionally and support automation efforts while contributing to scalable, high-impact analytics solutions

• As a Sr BI Analyst I, you will be responsible for working closely with many divisions of the company such as Product Development and Adoption, Technology, Performance, Growth, and Strategic Payer Partnerships. • This position develops moderately complex datasets, assists with complex dataset updates and modifications, and develops data visualizations and analyses that answer a broad set of questions across the company and begin to go deeper as a subject matter expert in at least one subdomain. • You work closely with other BI team members on a daily basis and have direct exposure with stakeholders across the company. • You will be knowledgeable in healthcare analytics, population health, and value-based care.

• Responsible for the execution of full reporting lifecycle; from design, development, testing, documentation, maintenance, and troubleshooting. • Complete work towards closing tickets, including triage, research, and communication with internal and external members. • Develop and update technical documentation for reporting systems. • Lead and drive requirement gathering meetings with experts in a variety of fields; defining systems scope and objectives of business requirements, including documentation of requirements (i.e. use cases) and relevant translation into system requirement specifications. • Other duties as assigned.

• Own the semantic layer end to end — Power BI models on Databricks and Fabric, built for performance, maintainability, and trust • Define the company’s metrics: one shared definition of AR days, denial rate, net collection rate, and the rest, so every team and every client sees the same truth • Build the provider-facing reporting our clients rely on — visually engaging, intuitive, fast, and credible enough to anchor a business review • Build the internal analytics our revenue cycle teams use to run their daily operation and to measure whether our automation is actually working • Establish our first data-analyst agents — automated analysis that monitors the data continuously, surfaces trends and anomalies, and drafts the first pass of insight before anyone thinks to ask • Shape the gold layer as its primary consumer — and take ownership of transformations if that’s in your toolkit • Set the BI standards, patterns, and review practices the function scales on as we grow • Sit with users on both sides — ops teams and client-facing leaders — and work problems, not ticket queues