• Collect and analyze trading data across various exchanges and asset classes. • Structure, organize, and maintain collected data in a clear and consistent format. • Perform reconciliations of financial trading data. • Aggregate and process data from multiple sources using Python. • Design, develop, and maintain automated workflows and integrations using no-code/low-code platforms (Make, n8n, Workato, or similar) to improve finance operations and reporting. • Identify inefficiencies in existing processes and propose structured solutions to enhance automation and overall performance. • Collaborate with Finance teams and cross-functional stakeholders.

• As the Sr. Forward Deployed Engineer supporting Finance, you will operate as the embedded AI engineering partner for the Finance organization • Attend planning reviews, close cycles, forecasting discussions, operational reviews, and executive preparation processes to deeply understand how Finance operates today and how AI can transform it tomorrow • Partner closely with the Sr. Director, Strategic Finance, who owns the Finance AI roadmap and business prioritization • Design and build the Finance-specific AI integration layer that connects AI systems to enterprise finance platforms, operational data, and institutional knowledge sources • Build AI-enabled quality assurance and validation systems that improve confidence, consistency, and operational rigor across Finance workflows • Develop AI systems that continuously analyze operational and financial processes to surface insights, anomalies, optimization opportunities, and business risks • Collaborate across Finance, Accounting, IT, Security & Compliance, Data & Engineering, and Enterprise AI & Automation teams • Partner closely with Finance SMEs to ensure workflows remain operationally accurate, transparent, and trusted. • Enable Finance teams to effectively evaluate, use, and extend AI systems over time.

• Own budgeting, forecasting, and annual planning for Engineering, Product, Detection & Response, SOC, and G&A functions • Develop and maintain cost models that connect infrastructure investments, cloud consumption, and operating expenses to business outcomes • Partner with Engineering and Product leaders on hiring plans, capacity modeling, contractor strategies, and investment prioritization • Lead vendor and SaaS spend reviews, identifying opportunities to optimize costs while maintaining operational effectiveness • Deliver variance analysis and forward-looking insights that help leaders understand both performance and future implications • Build analytical frameworks that support strategic decisions around growth, efficiency, and resource allocation • Partner closely with Accounting, Procurement, and business leaders to improve forecasting accuracy and financial visibility • Leverage AI tools and automation to improve analytical throughput and eliminate low-value manual work

• Own recurring revenue reporting workflows - daily/weekly file maintenance, revenue trackers, attainment dashboards, and variance analysis - ensuring accuracy and timely delivery at a daily cadence • Prepare and update executive materials for KPI reviews, Board of Directors presentations, and SLT meetings, including slide updates, and supporting data files • Conduct variance analysis on revenue movements and deliver clear, concise commentary that explains the "what" and the "why" behind performance trends • Support quarterly sales target-setting - reconciling forecasts and flagging areas of risk and opportunity for leadership discussion • Own the commercial commission review process - synthesizing attainment data, identifying trends, and providing analysis that informs leadership's compensation and incentive decisions • Execute ad-hoc analysis for Revenue, GTM, and Commercial leadership to support in-quarter decision-making • Maintain and improve core financial reporting infrastructure - identifying opportunities to enhance accuracy, reduce manual effort, and improve consistency across deliverables • Partner cross-functionally with Revenue, Sales Operations, and GTM teams to understand business drivers and translate them into financial context • Apply a common-sense quality check to all outputs - flagging anomalies, verifying data integrity, and ensuring deliverables are clean and free of error • Provide reliable coverage on all recurring deliverables during high-volume periods • Exercise independent judgment in prioritizing analyses and sequencing deliverables to maximize impact for commercial leadership.