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. 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. 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
The Machine Learning Engineering Manager is responsible for the whole lifecycle of our ML modeling function from the feature generation to the model rollout (design, development, deployment and monitoring), leading a talented team of machine learning engineers to develop, optimize and deploy ML models that power our fraud detection, credit risk and other applications like cross-sell, churn and collections; continuously improving the quality and performance of our models by gathering and integrating new data sources that enhance our predictive capabilities.
Responsibilities
- Lead and manage a team of machine learning engineers to deliver high-quality and scalable ML models.
- Provide mentorship, guidance and career development to the ML engineers in the team, fostering a culture of collaboration and innovation by encouraging experimentation and adopting best practices and new technologies in DS/ML.
- Drive the development of new machine learning models to be delivered on each of our markets and ensure they are production-ready, optimized for scale and continuously improved based on feedback from our stakeholders and performance on production.
- Collaborate with global teams including Risk, Fraud, Engineering and Product to deliver world-class data science products to international markets.
- 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
- 5+ 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.
- Strong leadership and people management skills with at least 2 years of experience leading and scaling high-performing teams.
- 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.
Finance for the next billion * Ownership * Break Through Walls * Live Communication * Transparency & Directness * Focus on Scale * Work-Life Balance * Embrace Diversity * Speed * Active Listening
•
Last updated on Jan 13, 2025