Analyst II, Full Stack

<div class="content-intro"><p>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.</p></div><p>The Fraud Strategy and Analytics team is responsible for analyzing, developing and optimizing Affirm's online fraud decisioning strategy. The team works cross-functionally with Product, Engineering, Operations, and Finance teams to define and ensure accurate execution of the fraud strategy to effectively prevent fraud losses.</p> <p>This role requires extensive use of data analytics to derive insights and develop/update fraud strategies, collaborating with cross-functional partners. Full stack analyst works with the Product teams to develop new fraud features, with the engineering team to launch online experiment to test out the performance of the new features, with the Operation team to execute risk and resolution strategies, with the Finance team to help facilitate discussions on portfolio performance and loss forecasting. </p> <p>Come join us in our mission to change consumer finance through better data and technology, lower costs, and increased transparency while providing the best customer experience.</p> <p><strong>WHAT YOU’LL DO </strong></p> <ul> <li> <p>Proactively explore data and identify opportunities to help accelerate product development or improve existing products in Trust and Safety, and drive the analytical work of online experiment to optimise the existing strategies to achieve better conversion rate.</p> </li> <li> <p>Translate analysis and trends into recommendations for business logic to improve identity and fraud conversion rates or fraud rates</p> </li> <li> <p>Develop scalable frameworks to manage tiered cutoffs for proprietary fraud machine learning models</p> </li> <li> <p>Evaluate innovative data sources to solve fraud risk, and partner with the data engineering team to develop and maintain the data pipelines for our core datasets for analytical purposes. </p> </li> <li> <p>Own end-to-end analytics workflow, including defining success and performance metrics, socialising them across the organisation, and creating actionable dashboards and reports</p> </li> <li> <p>Partner with Machine Learning on building fraud and identity verification strategies for new product, market, and user segments</p> </li> <li> <p>Partner closely with Product and Engineering to identify highest impact points in the funnel to drive user acquisition and retention</p> </li> </ul> <p> </p> <p><strong>WHAT WE LOOK FOR</strong></p> <ul> <li> <p>2-4 years work experience in customer risk management at a payments or financial company.</p> </li> <li> <p>Fluent in SQL and Python </p> </li> <li> <p>A team player with ability to collaborate and influence across different teams in the organisation</p> </li> <li> <p>Ability to clearly communicate findings and recommendations to both technical and non-technical audiences</p> </li> <li> <p>Passion to understand how the product works and how to change to make it more effective</p> </li> <li> <p>Strong time management skills and the ability to manage multiple projects and priorities</p> </li> <li> <p>Able to thrive in a fast-paced environment and be responsive and available during high intensity moments</p> </li> <li> <p>Bachelor’s or Master’s degree degree in a quantitatively rigorous discipline like engineering, statistics, math, or economics ... (truncated, view full listing at source)