Finance Analyst

Kaseya is the leading provider of AI-powered IT management and cybersecurity software, serving Managed Service Providers (MSPs) and internal IT organizations worldwide. Our comprehensive platform helps organizations efficiently manage, secure, and automate their IT environments, driving operational efficiency and long-term business success.

Backed by Insight Partners, a leading global software investor, Kaseya has experienced sustained double-digit growth and continues to expand its global footprint. Today, Kaseya supports customers in more than 20 countries and manages over 15 million endpoints worldwide.

Founded in 2000, Kaseya has built a culture centered around innovation, accountability, and results. We are a high-growth, high-performance organization that values individuals who are driven, adaptable, and committed to delivering exceptional outcomes for our customers and teammates alike.

At Kaseya, success comes from embracing challenges, moving with urgency, and continuously raising the bar. 

This role leads large-scale analytics initiatives across Finance Operations (order to cash), enabling automated insights, improved decision-making, and measurable business outcomes. The individual will partner cross-functionally to design robust datasets, build scalable analytical models and dashboards, and translate complex financial performance drivers into clear, executive-ready narratives.

• Lead initiatives to build intelligent insights and automated analysis workflows that improve efficiency and decision-making.
• Identify high-impact Finance Operations use cases and translate them into scalable analytical and decision-support solutions.

• Partner with Finance Operations, Data, and other cross-functional teams to design, scale, and automate financial data products and dashboards.
• Lead the design of scalable datasets, analytical models, and dashboards that enable forecasting, performance tracking, and risk management.
• Design robust datasets and perform complex SQL queries across multiple systems to ensure data accuracy, usability, and scalability.

• Lead complex analyses (e.g., revenue, cash flow, bad debt) to uncover drivers of performance and turn insights into measurable outcomes.
• Present insights to senior leadership and produce executive-level materials with clear, data-driven narratives.
• Influence cross-functional teams (Finance, Finance Operations, Sales, Data Engineering) by bringing structure to ambiguity and driving alignment.

• Bachelor’s degree in a quantitative or business field (e.g., Finance, Economics, Math, or related discipline).
• 2+ years of experience leading large-scale analytics initiatives or programs; SaaS and finance operations (order to cash) experience preferred.
• Proven experience building analytical or decision-support solutions (e.g., intelligent insights agents, automated analysis workflows).
• Strong SQL expertise, with the ability to design robust datasets and perform complex queries across multiple systems.
• Strong analytical depth and business acumen, with the ability to navigate ambiguity, uncover opportunities, and deliver clear, data-driven narratives.
• Experience applying advanced analytics techniques, including forecasting (e.g., revenue, cash flow, bad debt), segmentation, and regression analysis to identify drivers of performance.
• Strong written and verbal communication skills, including presenting insights to senior leadership and producing executive-level materials.
• Demonstrated experience influencing cross-functional teams with data (Finance, Finance Operations, Sales, Data Engineering).
• Proficiency in data visualization tools (e.g., Power BI, Sigma) and advanced Excel.
• Track record of operating effectively in ambiguous environments, driving clarity, and delivering measurable business outcomes.

• Advanced degree or relevant certifications (e.g., Master’s in Analytics, Business, or Finance).
• Familiarity with SaaS and financial/financial operations KPIs (ARR, TCV, churn, revenue, cash, billings, credit, risk, bad debt, payments, accounts receivable).
• Background in data modeling and building scalable analytics