• Lead and execute access and reimbursement strategy aligned with BridgeBio objective • Provide strategic direction and oversight for provider-facing reimbursement and access support • Identify access challenges across payer environments and drive compliant solutions • Serve as a senior subject matter expert on payer coverage, prior authorization, appeals, and reimbursement pathways • Lead, coach, and develop a team of Access & Reimbursement professionals (ARDs) • Establish performance expectations, provide ongoing feedback, and support professional development • Ensure consistent execution of access processes, tools, and compliance standards • Foster a collaborative, patient-focused, and accountable team culture • Maintain selective involvement in high-priority, complex, or escalated access and reimbursement cases • Provide hands-on expertise in challenging situations where senior leadership support is required • Model best-in-class, compliant field execution for the team • Partner with Commercial, Medical, Patient Services, Compliance, Legal, Trade, and Market Access teams • Share de-identified field insights related to payer trends, access barriers, and process gaps • Contribute to the development and refinement of access strategies, tools, and field materials • Ensure all access and reimbursement activities adhere to company policies and applicable laws, including HIPAA and OIG guidance • Maintain appropriate handling of patient information and ensure compliant, non-promotional engagement • Serve as a role model for ethical behavior and compliance standards

• Own the Full Data Function • Scale and advance our cloud-native data platform, driving architectural improvements that keep pace with rapid business growth • Architect data systems that serve both BI and ML workloads at increasing scale without sacrificing reliability or governance • Establish data governance, quality, and lineage frameworks that support compliance and rapid feature development • Serve as the single executive accountable for data ROI - what gets built, in what priority, measured by business impact • Coordinate distributed analyst governance across business units via dotted-line relationships with embedded analysts • Own the data science agenda - define where predictive modeling and statistical analysis create the most leverage • Drive delivery of core ML use cases: demand forecasting, EDD prediction, routing optimization, and warehouse intelligence • Establish experimentation frameworks that let the business run rigorous A/B tests and learn faster • Build feature engineering practices in collaboration with data engineering, ensuring data scientists have clean, model-ready inputs • Partner with the Decision Science PM to translate business problems into modeling priorities and communicate model outputs to stakeholders • Design and implement real-time streaming architectures that generate ML features at the freshness AI Engineering requires • Build and maintain feature stores that give data scientists and AI engineers consistent, versioned access to production features • Create training data pipelines that allow models to retrain reliably with high-quality, well-governed data • Define the interface between this team (feature generation, training data quality) and AI Engineering (model serving and deployment) - making handoffs clean and scalable • Ensure data infrastructure supports embedded analytics serving hundreds of customers with real-time operational insights • Assess data quality, infrastructure maturity, and integration complexity • Lead post-acquisition data integration, migrating acquired datasets into Stord's platform without disrupting existing operations • Establish repeatable playbooks for absorbing new data sources, schemas, and business logic from acquired companies • Partner with engineering and business stakeholders to prioritize which acquired data unlocks the most value, and sequence integration accordingly • Lead data engineering, data analytics, and data science as one team with a shared platform and a unified strategy • Build hiring and development frameworks that scale from today's 12-18 to a larger org as Stord grows • Create career paths across three distinct disciplines - engineers, analysts, and scientists - while maintaining a cohesive team culture • Develop the next generation of data leaders within the org; this role is designed to be a stepping stone for future directors of data engineering and data science • Partner with AI product managers across three tracks (AI Product, Decision Science, Internal Enablement) to align data priorities with product delivery • Enable demand planning, EDD prediction, and warehouse optimization features by ensuring the underlying data and models are production-ready • Build data products that contribute directly to revenue growth, operational efficiency, and customer retention • Establish SLAs and monitoring ensuring 99.9%+ uptime for business-critical data and model serving systems

• Develop, lead, and manage Playworks’ corporate giving strategy, including sponsorships, corporate partnerships, employee engagement programs, and workplace giving. • Build and manage a personal portfolio of corporate donors, cultivating relationships with senior corporate leaders, CSR teams, and community investment officers. • Identify, research, and cultivate new corporate funding opportunities aligned with organizational priorities. • Track and forecast revenue from corporate partnerships; maintain accurate database records for pipelines, deadlines, and deliverables. • Lead cross-functional partnership meetings to ensure deliverables are executed on time and with excellence. • Create tailored partnership proposals and pitch materials that communicate impact, ROI, and partnership value. • Monitor trends in corporate philanthropy and social impact to inform strategy and maintain competitive positioning. • Collaborate with program, finance, and marketing teams to design partnership packages, deliverables, and reporting requirements.

• Lead the creation and execution of a comprehensive, multi-regional development strategy to ensure required fund development targets are met annually. • Drive new revenue growth from institutional funders across a multi-region portfolio in Colorado, Indiana, Illinois, Minnesota, and Wisconsin. • Translate and align national development strategy into executable regional plans. • Implement a prescriptive fundraising model that provides structure and accountability.