Analyst II, Full Stack (Customer Servicing Analytics)

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.

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