About PayJoy
PayJoy is a mission-first financial service provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success.Β We lend through our patented technology that turns a smartphone into digital collateral, and our cutting-edge machine learning, data science, and anti-fraud AI allow us to offer the lowest cost and qualify the most customers in the industry.Β As of 2024 we have brought billions of dollars in credit to 12 million customers, doubling in the last two years while remaining strongly profitable and sustainable for the long term.
This role
As a Machine Learning Engineer, you will be responsible for developing, optimizing and deploying ML models that power our fraud detection, credit risk and other applications like cross-sell, churn and collections.
You will work closely with risk, fraud, engineering, product and business stakeholders across diverse markets to drive the design, implementation and scaling of ML models. Your role will also involve ensuring that we are continuously improving the quality and performance of our models by gathering and integrating new data sources that enhance our predictive capabilities.
You will own the whole lifecycle of our ML models, from the feature generation to the model rollout (design, development, deployment and monitoring).
You will be part of a data science team on a mission to improve access to credit and technology in emerging markets with the opportunity of creating a big and real positive impact to our millions of users across the countries we operate in.
PayJoy is proud to be an Equal Employment Opportunity employer and we welcome and encourage people of all backgrounds. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
Finance for the next billion * Ownership * Break Through Walls * Live Communication * Transparency & Directness * Focus on Scale * Work-Life Balance * Embrace Diversity * Speed * Active Listening