Data Analyst, Finance (Remote - US)

This position is posted by Jobgether on behalf of Vercel. We are currently looking for a Data Analyst, Finance in United States.

This is a high-impact opportunity for an experienced data analyst to work at the intersection of finance, analytics, and product usage. In this role, you’ll transform raw telemetry data into financial insights that directly shape strategic decisions around revenue, growth, and margin optimization. You’ll collaborate closely with FP&A, monetization, and engineering teams to build advanced models, simulations, and dashboards. Your work will drive clarity on SaaS economics, forecast performance, and power executive decision-making in a fast-paced, product-led environment.

Accountabilities:

• Build and maintain production-grade models in dbt and Snowflake to convert usage data into revenue, margin, and unit economic metrics.
• Design Python-based forecasting simulations (e.g., Monte Carlo, statistical models) to project usage, revenue, and cost trends.
• Lead root-cause analysis of financial performance, explaining key variances and identifying actionable insights.
• Partner with monetization and finance teams to model pricing experiments and quantify tier, overage, or feature impact.
• Deliver automated reporting through dashboards using tools like Looker, Mode, or Hex for Finance and executive stakeholders.
• Ensure high data accuracy by defining validation and quality frameworks for key financial metrics.
• Mentor peers across analytics and data engineering teams in best practices related to dbt, Python tooling, and Snowflake optimization.

Requirements

• 7+ years of experience in finance-focused data analytics or data science roles, ideally within SaaS or usage-based models.
• Expertise in dbt for building, testing, and deploying robust data pipelines; strong hands-on experience with Snowflake.
• Proficiency in SQL and Python (pandas, scipy/statsmodels, Prophet) for analysis, scenario planning, and statistical modeling.
• Deep understanding of SaaS and cloud unit economics, including ARR/MRR, COGS, payback, LTV/CAC, and retention cohorts.
• Demonstrated success in creating financial models from raw event data and leading data-backed monetization strategies.
• Skilled communicator who can translate technical insight into executive-level recommendations.
• Experience with BI platforms such as Looker, Mode, Hex, or Tableau, and familiarity with CI/CD in analytics workflows.
• Bachelor’s or Master’s degree in Finance, Statistics, Data Science, Economics, or a related discipline.

Benefits

• Competitive salary with equity-based compensation.
• Inclusive healthcare coverage.
• Flexible time off and generous vacation policy.
• Remote-friendly work environment with a budget to equip your workspace.
• Annual learning and development allowance for conferences, mentorship, and career growth.
• Salary range (San Francisco): $148,000–$222,000 USD, adjusted based on experience and location.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

#LI-CL1