• Ensure standardization, organization and reliability of the company's information • Enforce data usage, access and control policies • Ensure the quality, consistency and currency of critical data • Identify and correct inconsistencies, duplicates and errors • Map and document data sources • Structure and organize databases/data repositories • Perform analyses to support strategic and operational decision-making • Develop and maintain data models • Promote a data-driven culture

• Own analytics and AI-enabled workflow workstreams, from problem framing and stakeholder alignment to solution design, insight generation, adoption, and measurable business impact • Partner closely with Finance stakeholders to understand planning, forecasting and reporting workflows, and identify opportunities to improve them through data, automation, and AI • Translate Finance and business challenges into structured analytical frameworks, including data modeling, KPI design, forecasting, experimentation, and decision-support workflows • Design and build scalable data products, including pipelines, tables, dashboards, reporting layers, and AI-ready datasets that enable automated, flexible, and action-oriented Finance analytics • Build and test prototypes for AI-enabled Finance workflows, such as automated business review narratives, anomaly detection, variance explanation, forecast drivers, natural-language insight discovery, and self-service reporting • Partner with Data Engineering, Finance Systems and central data teams to move prototypes into reliable, governed, production-ready solutions • Contribute to defining and standardizing KPI frameworks for financial metrics ensuring alignment across Finance and business teams • Design dashboards, reporting solutions, and self-service analytics experiences that improve adoption, reduce manual reporting, and help business partners make faster, more consistent decisions • Analyze business and financial metrics to uncover key drivers of growth, retention, churn, productivity, and efficiency, and recommend clear data-backed actions • Contribute to scalable, repeatable analytics frameworks and best practices that improve Finance decision-making and create consistency across planning, forecasting, reporting, and business reviews • Apply strong governance, quality control, and documentation practices to ensure AI-enabled workflows are accurate, explainable, secure, and appropriate for Finance decision support • Communicate insights, recommendations, and roadmap tradeoffs to stakeholders and leadership through clear storytelling, executive-ready presentations, and concise written narratives

• Partner with distributed data teams to build, iterate, and optimize our corporate data architecture • Design, build, and maintain production-quality dashboards and scalable data products • Build advanced analytical models to unlock deeper insights into customer behaviors and macro trends • Synthesize complex data and analyses into compelling, structured narratives and actionable insights for executive consumption • Lead cross-functional projects to develop datasets • Set a high bar for analytics integrity across the organization

• Collaborate with business stakeholders in helping identify which metrics are the most useful to track, how should they be defined, and how can they be improved. • Provide ideas backed by analysis on how to improve status quo and finding new solutions and levers to improve business and clinical efficacy. • Build relationships and trust with business partners. • Use data, information, analysis and modeling to find ways to improve key metrics, optimize operations and clinical efficacy. • Partner closely with the Data Warehousing team function in designing business-facing semantic layers (data marts) and foundational information structures that’ll feed into analytics. • Serve as a subject matter expert for business rules and logic (clinical and non-clinical) to convert information into operational and clinical metrics and KPIs. • Partner with the Data Warehousing team in the design and development of a single source of truth repository for the company’s clinical and operational data. • Communicate effectively to business users, stakeholders and leaders on how business and clinical logic is applied to information points to arrive at key KPIs and metrics, why we’re measuring what we’re measuring, and how operational activities interlink to KPIs, OKRs etc. • Help with the build-out and maintenance of an enterprise KPI catalog and dictionary. • Actively participate in KPI/metrics governance. • Work with influence, without ego and exhibit a collaborative spirit, with an unyielding motivation to do what’s best for the organization. • Complete all required documentation in a timely and accurate manner. • Protect privacy and maintain confidentiality of all company procedures and information about team members, participants, and families. • Follow WelbeHealth policies and procedures and participate in any required Quality Improvement activities, staff training and meetings.