• Learning all about the core business of information exchange / release of information in healthcare • Diving deep with customers, sales, customer success, operations, product, data engineering, and business intelligence teams on key reporting, analytics, and productivity measurement needs • Developing a clear understanding of Datavant’s internal and customer-facing reporting experiences, including Healthsource, Provider Console, and other downstream applications where users consume reporting insights • Partnering with Data Engineering and Business Intelligence to clarify the operating model for reporting and data products, including how user needs become data requirements, reporting deliverables, dashboard experiences, and roadmap priorities • Creating and socializing a reporting and data product roadmap that balances customer reporting needs, internal operations needs, dashboard user experience improvements, and Healthsource productivity instrumentation • Identifying quick-win improvements to existing reporting experiences that help customers and internal teams better understand performance, productivity, status, and opportunities for improvement • Defining success metrics for reporting adoption, user satisfaction, data quality, dashboard usability, and operational productivity insights

• Separate durable preference from noise. Design robust feature representations from high-cardinality, implicit behavioral data (swaps, skips, saves) to capture true user intent and predict future engagement. • Model temporal dynamics and changing tastes. Architect sequential and recency-aware systems that adapt to shifting user preferences, ensuring recommendations reflect current intent rather than stale history. • Solve the cold-start problem. Leverage cohort signals, clustering, and content embeddings to generalize learnings across users, ensuring that even a new customer’s first box feels deeply personalized. • Bridge ML and constrained optimization. Integrate model scores (e.g., predicted conversion) with operations-research engines to perform business-aware re-ranking, balancing personalization with hard constraints like diet, budget, and inventory. • Advance the modeling. Evolve our systems using the architectures that drive modern, high-scale personalization, such as multi-stage retrieval and ranking, learning-to-rank (LTR), matrix factorization, and gradient-boosted trees. You will also evaluate and integrate more sophisticated techniques (like contextual bandits or sequence modeling) as our data complexity grows. • Drive rigorous experimentation. Define robust offline evaluation metrics (e.g., NDCG, MAP) and design online A/B tests to measure true causal impact on customer retention and satisfaction

• Own the definition, consistency, and integrity of Oura’s core business metrics across product, finance, and go-to-market. • Establish and maintain a unified “metrics layer” that ensures a single source of truth for executive and operational decision-making. • Resolve ambiguity in metric definitions and drive alignment across senior stakeholders when competing interpretations exist. • Ensure critical KPIs are consistently defined, reproducible, and trusted across the organization. • Partner with the CFO’s office and FP&A to define, document, and deliver the financial KPIs that show up in Board and exec reporting including but not limited to (Revenue, Gross profit/margin, adjusted EBITDA, Net Income, Units Sold, Warranty Rate, Membership, Engagement, and Retention and the long tail of corporate metrics). • Establish each financial KPI as a governed, audit-grade data product — locked definitions, single owner, quality tests, full lineage to source systems, formal sign-off by key stakeholders, and a documented change-management process. • Treat key data pipelines and metrics as production-grade systems with defined reliability standards. • Establish monitoring, validation, and escalation processes for data issues affecting tier-1 business metrics. • Drive structured incident management processes for data breaks, metric regressions, and reporting inconsistencies. • Improve end-to-end data quality across systems of record, transformation layers, and reporting tools. • Ensure the analytics delivered in external audit cycles — documentation, walk auditors through lineage, and ensure SOX-aligned controls and segregation-of-duties practices are reflected in how financial metrics are produced. • Coordinate large-scale initiatives spanning Data Engineering, Analytics, Finance, GTM, Product, Operations, and Technology. • Manage complex dependencies across business and technical systems to ensure consistent data flow and logic. • Establish governance forums and decision frameworks that ensure clarity, accountability, and fast resolution of tradeoffs. • Translate fragmented systems into coherent operating models that support scalable decision-making. • Design how data is used to drive planning, forecasting, and resource allocation across the company. • Partner with Finance and BizOps to ensure planning systems are grounded in consistent, trusted data. • Build mechanisms that connect operational metrics to strategic decision-making and executive prioritization. • Enable faster, higher-confidence decisions by improving signal clarity and reducing ambiguity in core business data. • Translate complex technical and systems challenges into clear, decision-oriented narratives for executives. • Provide structured updates on data health, system integrity, and transformation progress. • Drive organizational adoption of standardized metrics, reporting systems, and data definitions. • Influence without authority across senior leaders to ensure alignment on the “one version of truth.”

• Serve as the primary point of contact for SCCAF-related coordination between clients, contractors, and Olsson's engineering teams. • Manage SCCAF project schedules and align study milestones with construction timelines. • Coordinate the development and delivery of SCCAF reports, settings, labels, RFIs, and submittals. • Monitor project progress, identify potential risks, and proactively resolve issues that could impact schedule or quality. • Lead SCCAF coordination meetings, document action items, and ensure timely follow-through from all stakeholders. • Facilitate resolution of technical and data-related challenges, including equipment information, field discrepancies, and design revisions. • Manage the SCCAF process from project kickoff through final deliverables while maintaining accurate documentation and study records. • Support overall project operations, including invoicing coordination, document control, deliverable tracking, and quality assurance processes.