Financial Analyst

CommerceIQ is building the AI platform that runs commerce for the world's largest brands. We are not selling AI demos. We are shipping AI agents for content, media, and sales into the workflows of the Fortune 100 every week.

Customers include Coca-Cola, Nestlé, Colgate-Palmolive, Mondelez, Samsung, and Kellogg's. Backed by SoftBank, Insight Partners, and Madrona. Headquartered in Mountain View with teams across the US, India, Canada, and the UK. Pre-IPO.

As a financial analyst, you’ll be a key partner to our business teams, turning data into clear insights that guide how we plan, invest, and grow. You’ll own recurring reporting and forecasting, support budgeting, and dig into the numbers behind our business. You’ll work closely with Sales, Customer Success, Product, and Engineering, and your analysis will shape real decisions.

• →Build and maintain financial models, forecasts, and budgets, including ARR, bookings, revenue, and operating expense
• →Prepare monthly, quarterly, and annual reporting, including variance analysis and commentary for leadership
• →Partner with department leaders on headcount planning, spend tracking, and budget-to-actual reviews
• →Track, maintain, and analyze KPI’s
• →Support the month-end close process by working with Accounting
• →Create board and executive materials that explain performance clearly and concisely
• →Find ways to automate reporting and improve data quality across systems
• →Ad hoc analysis that helps us move faster and make better decisions

• Bachelor’s degree in finance, accounting, economics, or a related field
• [2–4] years of experience in FP&A, corporate finance, investment banking, or a similar analytical role, ideally at an AI or technology company
• Advanced Excel and Google Sheets skills, including strong financial modeling
• Solid understanding of three-statement models, budgeting, and forecasting
• Clear communication skills, with the ability to explain complex numbers to non-finance partners
• Strong attention to detail and comfort working with large datasets
• Curiosity and a bias toward action in a fast-paced environment