Data Analyst, Finance

Finance Data Analyst

About Vercel:

Vercel provides developers with the tools and cloud infrastructure necessary to build, scale, and secure a faster, more personalized web. As the team behind v0, Next.js, and AI SDK, Vercel empowers customers such as Ramp, Supreme, PayPal, and Under Armour to build for the AI-native web.

Our mission is to enable the world to ship the best products. This begins with creating an environment where everyone can perform at their best. Whether you are building on our platform, supporting our customers, or shaping our narrative, you can simply ship things.

About the Role:

As a Finance Data Analyst, you will serve as the technical bridge between Finance and Data. You will be responsible for the financial analytics stack, delivering reliable models, dashboards, and simulations to assist leadership in understanding how usage-based revenue flows through the business, identifying margin opportunities, and forecasting growth. You will collaborate daily with FP&A, Product Monetization, Data Engineering, and Executive Leadership to transform complex usage signals into actionable financial insights.

Responsibilities:

• Model usage-based economics: Build and maintain dbt models in Snowflake to translate raw product telemetry into ARR, margin, and unit-economics views.
• Forecast revenue & costs: Design Python-driven Monte Carlo and statistical models to project usage, revenue, and gross margin under various scenarios.
• Run variance & root-cause analyses: Explain plan-vs-actual variances across revenue, COGS, and operating expense lines; identify key drivers.
• Simulate pricing & packaging changes: Partner with Product Monetization to quantify the impact of new tiers, overage bands, and feature gates.
• Automate financial reporting: Deliver self-serve dashboards (e.g., Hex, Mode, Looker) that are trusted by Finance, ELT, and Board stakeholders for monthly close.
• Elevate data quality: Define testing, reconciliation, and data-quality SLAs to enable Finance to audit every revenue and cost metric back to its source.
• Mentor analysts & engineers: Provide best-practice guidance on dbt design patterns, Snowflake optimization, and Python analytical tooling.

Requirements:

• 7+ years in analytics or data science roles with a focus on Finance (SaaS or usage-based experience preferred).
• Deep hands-on expertise with dbt (production-grade models, testing, CI/CD) and Snowflake (performance tuning, RBAC, cost management).
• Advanced SQL + Python (pandas, scipy/statsmodels, or Prophet) for forecasting, scenario modeling, and statistical analysis.
• Strong understanding of SaaS / cloud unit economics—MRR/ARR, COGS allocation, gross margin, payback, LTV/CAC, cohort retention.
• Demonstrated success in building usage-based pricing and forecasting frameworks from raw event data.
• Comfortable communicating insights to executive audiences and collaborating with engineers on data details.
• Experience with BI / notebook tooling (Looker, Hex, Mode, Tableau, or similar) and data transformation tools like dbt.
• Bachelor's or Master's degree in Finance, Economics, Statistics, Data Science, or a related field.

Benefits:

• Competitive compensation package, including equity.
• Inclusive Healthcare Package.
• Learn and Grow - we provide mentorship and send you to events that help you build your network and skills.
• Flexible Time Off.
• We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed.

Compensation:

The San Francisco, CA base pay range for this role is $148,000-$222,000. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location, and the total package includes benefits and equity-based compensation. Your recruiter can share more details during the hiring process.

Company Commitment:

Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression...