Analyst II, Full Stack (Fintech)

TL;DR

Analyst II, Full Stack (Fintech): Developing and optimizing forecasting models for customer servicing strategy with an accent on capacity planning and staffing for global launches. Focus on embedding AI/ML into analytics workflows and building automated systems for infrastructure demand forecasting.

Location: Remote (Must be based in the US)

Salary: $128,000 - $205,000 per year

Company

Affirm is a fintech company reinventing credit to provide honest and friendly buy-now-pay-later options without hidden fees.

What you will do

• Own planning and staffing for UK and new geography launches, maintaining guardrail metrics.
• Build and maintain forecasting models using time series, regression, and ML for headcount and budgeting.
• Develop demand forecasts for checkouts and app opens across CA, UK, and other geographies.
• Collaborate with cross-functional partners to frame planning problems and support high-quality decisions.
• Analyze productivity and efficiency improvements using financial performance data.
• Integrate AI/LLM tooling across the analytics workflow to automate manual tasks.

Requirements

• Degree in a quantitative field such as Statistics, Industrial Engineering, or Operations Research.
• 5+ years of experience solving forecasting or quantitative problems.
• Proficiency in SQL and Python or R.
• Experience with cloud-native data platforms such as Databricks, Snowflake, or BigQuery.
• Hands-on experience integrating AI/LLM tooling into analytics workflows.
• Must be based in the United States.

Nice to have

• Experience building optimization models using linear programming (e.g., CPLEX, Gurobi).

Culture & Benefits

• Remote-first work environment with flexibility to work almost anywhere in the US.
• 100% subsidized medical coverage, including dental and vision for dependents.
• Generous flexible spending wallets for technology, food, and lifestyle needs.
• Competitive vacation and holiday schedules for recharging.
• Employee Stock Purchase Plan (ESPP) allowing discounted share purchases.