Analyst Ii, Full Stack

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. We're looking for intelligent, driven professionals to join our team. The Operations Analytics team uses data to shape servicing strategy across contact channels, customer segmentation, capacity planning, forecasting, and repayment operations. The ideal candidate brings strong analytical depth, systems thinking, and the ability to partner cross-functionally to drive meaningful business impact. AI is integral to the analytics workflow on this team. The analyst applies AI from data exploration through model validation to stakeholder communication, and helps shape how the team uses it. The role requires architectural decisions, strong stakeholder alignment, and embedding AI/ML in core decisions. Operating independently in ambiguous environments is essential. What You'll Do Scope Planning: Own planning and staffing for UK and new-geography launches and special teams. Develop and maintain the guardrail metrics. Foundations: Build working familiarity with the underlying data, including demand signals, agent rosters (team, title, country), and agent activity (delivered hours, status), and license demand. Infrastructure forecasts: Own demand forecasts for checkouts and app opens in CA and UK and new geographies. Insights: Report on forecast health for UK, CA, and other geos (accuracy and outlook). Advise Customer Operations real-time management (UK) on agent productivity. Curate AI knowledge for Customer Operations (UK) and UK Infrastructure forecasting. Responsibilities Build and maintain forecasting models, using time series, regression, and machine learning, to support contact forecasting, headcount and license planning, and budgeting. Partner with stakeholders to frame planning and forecasting problems, develop supporting metrics and diagnostics, and support high-quality decisions. Surface productivity and efficiency improvements using budget and financial performance data. Present recommendations to leadership, drive timely decisions, and communicate clearly with cross-functional partners. Partner with operational planning and other analytics teams to understand the business context for headcount and workforce scheduling, and get the data needed for accurate forecasts. Stay current on the business and our changing technical environment. What We Look For Bachelor's, Master's, or PhD in a quantitative field (e.g., statistics, industrial engineering, operations research) and 5+ years solving forecasting, planning, or related quantitative problems. Strong proficiency in SQL and Python or R, and hands-on experience with a modern cloud-native data platform (e.g., Databricks, Snowflake, BigQuery, or equivalent). Hands-on experience using AI/LLM tooling across the analytics workflow: writing, validating, and iterating on AI-generated SQL and Python, and integrating AI outputs into analyses that stakeholders trust. Experience building optimization models using linear programming techniques (e.g., CPLEX, Gurobi) is a plus. Strong experience developing and validating statistical forecasting models, with disciplined approaches to performance measurement, backtesting, and robust error tracking. Proven abili