• Build, streamline, and automate recurring data models and reporting processes to reduce manual workload. • Own large, complex financial and operational datasets (NetSuite, marketplace reports, external files) and translate them into usable formats. • Develop sophisticated Excel and/or BI dashboards (Power BI etc.) for financial and operational performance tracking. • Partner with Finance and Accounting teams to provide analytical support for key business questions (COGS allocation, SKU profitability, channel analysis, etc.). • Support month-end and quarter-end reporting by structuring large data extracts into reconciled reporting packages. • Assist in variance analyses across sales channels, products, and cost drivers to identify risks and opportunities. • Identify inefficiencies in current manual processes and propose/implement data-driven solutions. • Support automation initiatives that enable scalability of reporting and analysis. • Collaborate cross-functionally (Finance, Accounting, Supply Chain, IT) to ensure data integrity and improve upstream inputs. • Take a leading role in ad hoc data pulls and analysis to support decision-making. • Assist in the preparation of financial presentations (financial views, slides, etc.) • Provide support for strategic projects e.g., pricing automation, channel expansion etc.

• Own the data architecture and data mapping required to support the growing B2B reporting needs • Deliver key performance insights through regular and ad-hoc analysis to drive further investment and evolution of Omada programs • Develop and support well-designed Tableau dashboards (or similar BI tools) • Organize a cross functional team to manage workstreams related to your analytics, like Performance Guarantees or Program Incentives • Work closely with various data teams to improve data quality and standardize reporting • Define operational processes and support system enhancements that drive analytics and reporting support at scale • Collaborate across multiple teams including analytics, data science, data engineering and architecture, clinical, and product • Explore and integrate applications of AI into analytics use cases

• Gathering relevant company contact information, such as email addresses, job titles, and external and URLs (i.e. LinkedIn), for cold outreach and marketing campaigns • Ensuring 100% data quality and accuracy, meticulously verifying the accuracy of the data to ensure that the data can be trusted for further use • Identifying potential leads and prospects; sourcing contact information for those parties • Assistance in the creation of marketing campaign performance reports and supporting analyses • Interpreting data, analyzing results using statistical tools, and providing ongoing reports on marketing campaign performance • Providing quality analysis and assurance for imported data from various external sources • Alignment of contact sourcing strategies with overall business goals and marketing activities • Clear arrangement of the data in accordance with the demands of various projects • Organizing CRM and contact information data into lists that are tailored to meet the data quality requirements • Periodic reviews and CRM contact database updates to ensure data accuracy and usefulness

• Develop, execute, and optimize SQL queries to retrieve data from relational databases and big data environments. • Analyze datasets to identify relevant trends, patterns, and correlations. • Synthesize complex findings into structured reports and presentations, communicating technical results to technical and non-technical stakeholders clearly and effectively. • Partnering with cross-functional teams and stakeholders to identify core business questions and translate complex datasets into actionable analytical insights. • Ensuring data quality, governance, and compliance across all systems. • Working with and supporting Technical Leaders in project execution and timely delivery. • Collaborating with client teams.