Machine Learning Engineer - Fraud
TLDR
Own end-to-end fraud ML models from feature generation to deployment across PayJoy's products and global markets, building scalable pipelines and production-ready systems.
Ensure our delivered ML models are production-ready, optimized for scale and continuously improved based on feedback from our stakeholders and performance in production.
Improve our infrastructure for fraud decisioning by extending it to new entity types, identifying and constructing new rules, and supporting greater scale as we grow.
Handle large, complex datasets to clean, preprocess and extract relevant features to improve product 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.
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 lifecycle: 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 fraud detection or other applications of machine learning in the financial market is a big plus.
Experience with LLMs or graph databases is also a plus.
Hands-on experience with Databricks for developing, deploying and monitoring machine learning workflows at scale is another plus.
Good verbal and written communication skills in English
Ability to work in a fast paced environment with constant requirement changes.
Benefits
Free Meals & Snacks
Catered lunches
Health Insurance
Life insurance.
Home Office Stipend
$2,000 MXN monthly grocery coupons
Learning Budget
$2,000 USD annual Professional Development perk
Paid Time Off
50% Vacation premium
Stock Options
13% Saving funds
Wellness Stipend
Phone finance, Headphone, home office equipment and wellness perks.
PayJoy is a credit provider focused on empowering under-served customers in emerging markets to achieve financial stability. Our patented secured credit technology opens the door for these individuals to access credit systems through innovative point-of-sale financing and credit cards. By leveraging machine learning and data science, we help our customers thrive as micro-entrepreneurs and navigate economic challenges effectively.
- Founded
- Founded 2015
- Employees
- 51-200 employees
- Industry
- Internet Software & Services
- Total raised
- $86M raised