The Role
The Machine Learning Engineer will develop and optimize ML models for fraud detection and credit risk, collaborating with global teams and improving model performance through integrated data sources.
Summary Generated by Built In
About PayJoy
PayJoy is a mission-first credit provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success. Our patented technology for secured credit provides an on-ramp for new customers to enter the credit system. Through PayJoy’s point-of-sale financing and credit cards, customers gain access to a modern quality of life. PayJoy’s credit also allows our customers to seize opportunities as micro-entrepreneurs, and provide safety acts as insurance for tough times. Through our cutting-edge machine learning, data science, and anti-fraud AI, we have served over 17 million customers as of 2025 while achieving solid profitability for sustainable growth.
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.
Responsibilities
- Collaborate with global teams including Risk, Fraud, Engineering and Product to deliver world-class data science products to international markets in Latam, South Africa and APAC.
- Design, build, and deploy machine learning models for a variety of use cases, including fraud detection, credit risk modeling, customer segmentation, collections, and churn.
- Ensure our delivered ML models are production-ready, optimized for scale and continuously improved based on feedback from our stakeholders and performance on production.
- Handle large, complex datasets to clean, preprocess and extract relevant features to improve model accuracy and performance.
- Write production-level code with documentation, testing and peer review.
- Work with a data-driven mindset and understand the critical importance of handling data properly and safely.
- Lead the testing, cost-benefit analysis and integration of new data sources to improve the accuracy and robustness of our ML models.
- Work closely with our ML Platform and Tooling team to design and implement scalable feature generation and extraction pipelines and model deployment/monitoring processes.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- 3+ years of experience as a data scientist, machine learning engineer, data engineer or a closely related position with a proven track record of writing production-level code and developing and maintaining ML models in production.
- High proficiency in Python and a strong understanding of its related libraries and frameworks (e.g., Scikit-Learn, Pandas, Flask, etc).
- Comprehensive knowledge of ML life cycle: from data extraction and feature engineering to model serving and monitoring for live and batch processing.
- Demonstrated experience with cloud providers (AWS preferred) and related services like containerization (e.g., Docker).
- Experience in credit risk modeling, fraud detection or other applications of machine learning in the financial market is a big plus.
- Good verbal and written communication skills in English.
- Ability to work in a fast paced environment with constant requirement changes.
Benefits
- *Local benefits will depend of the country of hiring*
- 100% Company-funded Health and Dental insurance for employees and immediate family members.
- Phone finance, Headphone, home office equipment and fitness perks.
- $2,000 USD annual Co-working Travel perk.
- $2,000 USD annual Professional Development perk.
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.
PayJoy Principles
Finance for the next billion * Ownership * Break Through Walls * Live Communication * Transparency & Directness * Focus on Scale * Work-Life Balance * Embrace Diversity * Speed * Active Listening
Top Skills
AWS
Docker
Flask
Pandas
Python
Scikit-Learn
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The Company
What We Do
PayJoy's mission is to deliver access to credit to the next billion people in emerging markets worldwide. Our unique mobile security technology gives customers the ability to afford their first smartphone on credit, using the phone itself as collateral, and then provides further access to credit to help weather life's unexpected financial surprises and climb the ladder of economic well-being.
Founded in 2015, today PayJoy has reached millions of customers in a dozen countries around the globe, including Mexico, Brazil, Colombia, India, Kenya, and South Africa, and is on a strong growth path with support from major industry partners to bring credit to the next billion emerging consumers.
