• Lead a team of Analysts supporting coordinated campaigns across the country • Develop a reporting roadmap for DNC’s states and voter registration programs • Communicate national expectations on voter contact universes; hold state Data teams accountable • Lead communication of regular updates from the states analytics team internally and externally • Collaborate with leaders across the DNC Data & Tech Teams

• Build end-to-end RCM dashboards in Power BI for new and existing clients. • Transform raw encounter, claims, payment, AR, and denial data into intuitive visualizations. • Develop KPI frameworks and executive-level dashboards (e.g., collections, denials, AR performance, coding trends). • Optimize data models for performance, accuracy, and refresh reliability. • Ensure all dashboards adhere to internal design standards, naming conventions, and SOPs. • Analyze healthcare RCM datasets to uncover trends, bottlenecks, and improvement opportunities. • Work directly with RCM and client teams to understand workflows and convert business rules into measurable KPIs. • Provide data-driven recommendations to improve reimbursement, throughput, and operational efficiency. • Use Databricks for data discovery, transformation, and validation. • Troubleshoot data quality issues and partner with engineers to ensure accurate pipeline execution. • Validate that received client data aligns with expected volume, structure, and completeness. • Develop predictive models such as denial prediction, payment probability, and cashflow forecasting.

• Serve as the primary analytics partner to HR and business leaders, understanding their challenges and translating them into analytical solutions. • Provide insights and recommendations that inform decisions on talent strategy, workforce planning, retention, and employee experience. • Build strong relationships with HRBPs, COEs, and leadership teams to ensure alignment on priorities. • Develop dashboards, reports, and analyses on workforce metrics (e.g., attrition, DEI, engagement, recruiting, performance). • Translate complex data into clear, actionable insights with strong storytelling and visualization. • Deliver executive-ready materials that connect people data to business outcomes. • Partner cross-functionally with analytics and technical teams to ensure data accuracy, resolve quality issues, and maintain consistent, reliable insights. • Use statistical analysis, predictive modeling, and trend forecasting to identify workforce risks and opportunities. • Guide stakeholders in building a data-driven culture within HR and across the business. • Drive adoption of self-service analytics platforms and democratize access to people insights.

• Design and implement scalable data pipelines to ingest, process, and transform large datasets (structured & unstructured). • Develop, validate, and optimize supervised and unsupervised machine learning models leveraging Python, SQL, and modern libraries. • Conduct feature engineering, model selection, and statistical modeling to deliver high-impact solutions. • Build and expose model APIs or containerized workflows for seamless integration and deployment in production environments. • Apply MLOps best practices to model versioning, testing, monitoring, and deployment. • Work with Big Data technologies such as Databricks and Snowflake to unlock analytics at scale. • Orchestrate complex workflows using tools like Airflow or Dagster for automation and reliability. • Collaborate with AI teams to refine prompt engineering and leverage AI tooling for model fine-tuning and augmentation. • Maintain familiarity with leading cloud platforms (AWS, Azure, GCP) for model training, deployment, and infrastructure management. • Partner with product, engineering, and business teams to translate requirements into technical solutions.