• Develop financial dashboards and reporting: Build, maintain, and enhance interactive dashboards that help stakeholders understand financial and business performance, identify trends, and make informed decisions. • Translate business questions into insights: Partner with internal stakeholders to understand analytical needs and deliver self-service reporting and actionable analysis across ARR, paying customer accounts, retention, subscriptions, and customer cohorts. • Strengthen financial data foundations: Contribute to reliable data models that support evolving pricing strategies, new product lines, and changing business models while maintaining consistent definitions for key metrics. • Support financial reporting cycles: Assist with month-end and quarter-end reporting by investigating variances, identifying performance drivers, and explaining changes in financial results. • Automate analytical workflows: Use AI tools and automation to reduce repetitive manual tasks, improve spreadsheet-based processes, and increase the speed and reliability of reporting. • Improve data quality and governance: Collaborate with Analytics Engineering to productionize reporting sources, validate data, resolve discrepancies, and maintain trusted analytical datasets. • Collaborate across departments: Present findings, incorporate stakeholder feedback, and work closely with Finance, Sales, Marketing, Revenue Operations, and Data Analytics teams to ensure reporting meets business needs. • Promote continuous improvement: Identify opportunities to refine dashboards, optimize analytical processes, and introduce more efficient, scalable approaches to financial analysis and reporting. Requirements • Analytics experience: Previous experience in data analytics or a related analytical role, with the ability to investigate complex datasets and translate findings into clear, actionable recommendations. • Strong SQL proficiency: Hands-on experience writing SQL queries using joins, common table expressions (CTEs), window functions, and other techniques to analyze large datasets. • Data modeling knowledge: Understanding of data modeling principles, including fact and dimension tables, star schemas, and methods for building consistent, reliable data structures. • Business and stakeholder collaboration: Ability to gather requirements, understand business questions, communicate analytical findings, and improve reporting solutions based on stakeholder feedback. • Financial and SaaS analytics: Experience working with Finance, Sales, or go-to-market data is an advantage, particularly in a SaaS environment. Familiarity with ARR, subscriptions, retention, billing, and customer cohort analysis is beneficial. • Business intelligence and AI tools: Familiarity with analytics and AI platforms such as Hex, Claude Code, Cursor, or comparable tools is an asset, along with an interest in applying AI to improve analytical workflows. • Data platform exposure: Experience with dbt and enterprise data sources such as Salesforce, Stripe, or NetSuite is considered an advantage. • Analytical problem-solving: Strong diagnostic skills, sound judgment, and attention to detail, with the ability to investigate discrepancies and identify underlying causes. • Communication and adaptability: Clear communication skills, a collaborative mindset, and the ability to manage changing priorities in a fast-paced environment. • AI responsibility: Willingness to use AI thoughtfully and responsibly, maintaining accuracy, confidentiality, data integrity, and appropriate controls while improving productivity. Benefits • Competitive US base salary: $95,000–$133,000 USD annually. • Equity compensation: Equity grant, with participation in applicable incentive programs. • Health and wellness: Comprehensive health insurance, including medical, dental, and other benefits. • Retirement savings: 401(k) plan with employer matching. • Time off: Generous paid time off to support rest and personal commitments. • Family support: Maternity and parental leave top-up programs. • Remote-first work: Flexibility to work remotely from within the United States, with occasional travel for team gatherings and in-person collaboration as required. • Professional growth: Opportunities to develop analytical expertise, explore AI-enabled workflows, and contribute to impactful projects in a collaborative environment. • Recognition and community: Peer-to-peer recognition programs and paid volunteer days. • Additional perks: Access to a complimentary password manager account and a culture that values transparency, collaboration, continuous learning, and individual contributions.