Analytics Lead, 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.

The Risk & Analytics team makes crucial decisions that direct Affirm’s business strategy. Our team designs and runs experiments to decide which product features to launch and which marketing campaigns to fund. We analyze performance not just to report on it, but to determine where to invest resources for maximum impact through building tools and analytical frameworks. We take ownership of the entire analytical lifecycle, from initial question to final business decision, ensuring Affirm grows efficiently and intelligently.

The POS Analytics team helps Affirm make its most important growth and investment decisions. We identify opportunities to expand the reach of Affirm’s products, optimize the consumer and merchant experience, and direct resources toward the highest-value opportunities. We own analytics end to end—from goal setting and performance tracking to opportunity sizing, rigorous decision support, and experiment design and measurement. We translate insights into actions that help Affirm grow efficiently and sustainably.

The POS Analytics team is looking for an Analytics Lead, Full Stack to support our next phase of growth with major platform partners. In this role, you will drive the growth strategy for these partnerships, identify and size growth opportunities, shape product and investment decisions, and measure the impact of key initiatives. You will work closely with our Strategic Partnerships, Product, Finance, Engineering, and Pricing teams. You should combine exceptional problem-solving and analytical skills with a general manager mindset, strong cross-functional leadership, and deep knowledge of the lending and/or payments space.

What you’ll do

• Own and prioritize the analytics portfolio for a significant product or business area, operating with a business owner mindset to define success, identify investment opportunities, recommend actions, and measure impact across customer experience, growth, risk, and profitability.
• Lead complex analyses that balance growth, credit performance, customer experience, and unit economics.
• Translate analytical findings into clear and compelling narratives and business cases that help leadership make informed decisions.
• Tackle ambiguous problems by identifying the core hypotheses and designing actionable experiments to validate product-market fit and economic viability.
• Lead through influence across Product, Engineering, Finance, and Revenue, building alignment around important decisions without formal authority.
• Build scalable data models, metrics, dashboards, and AI-assisted analytical workflows that improve access to trusted insights while maintaining rigorous validation, reproducibility, and data governance.
• Raise the impact of the analytics organization by mentoring analysts and developing reusable analytical practices and tools.

What we look for

• A General Manager mindset, strong product and credit risk judgment, and a track record of proactively identifying high-impact opportunities.
• Strong understanding of the consumer lending and credit industry, including lending economics, portfolio performance, and credit metrics. The strongest candidates will bring experience across both risk and product and understand the tradeoffs among growth, credit performance, customer experience, and profitability.
• The ability to perform complex analyses and translate the results into clear, actionable business recommendations.
• Exceptional communication and influencing skills across technical and non-technical audiences, including senior leaders.
• 6 or more years of experience in a cross-functional analytical role, with demonstrated impact on significant product, risk, or business decisions.
• Advanced SQL and Python skills, including statistical analysis, experimental design, and practical experience with A/B testing.
• Demonstrated curiosity and a growth mindset, with hands-on experience using AI-powered tools such as Cursor, Claude, or similar assistants to accelerate analysis, automate workflows, enhance problem-solving, and advocate for AI adoption across analytical workflows.
• The ability to independently prioritize a roadmap, manage multiple workstreams, and mentor other analysts.
• A bachelor’s degree in a quantitatively rigorous field—or equivalent practical experience. An advanced degree is a plus.