[Remote] Lead Fraud Data Scientist

Note: The job is a remote job and is open to candidates in USA. Félix is building a financial ecosystem for Latin immigrants in the U.S. and is seeking a Lead Data Scientist for their Fraud team. The role involves leveraging machine learning and data analysis to develop models that detect and prevent fraudulent activity in real-time, ensuring a trustworthy platform for users.

Responsibilities

• Define the long-term machine learning strategy for the fraud team, establish technical best practices, and mentor junior data scientists
• Own the entire lifecycle of fraud detection models, from data exploration and feature engineering to model training, validation, deployment, and monitoring
• Design and develop models specifically targeted at lending fraud typologies, including synthetic identity fraud, first-party loan default fraud, and application fraud
• Conduct deep-dive investigations into emerging fraud patterns and user behavior, using clustering, outlier detection, network analysis, and other unsupervised techniques to uncover hidden risks and organized fraud rings
• Design and execute A/B tests to measure the impact of new models, rules, and strategies on both fraud detection rates and user experience
• Partner closely with Product, Engineering, Risk, and Operations teams to translate business needs into data science solutions, seamlessly integrate ML scores with rule engines, and communicate complex results to non-technical audiences
• Deploy, monitor, and maintain machine learning models in a cloud environment, ensuring high availability and performance
• Build and maintain dashboards using tools like Tableau or Looker to track key performance indicators (KPIs) like fraud loss rates, false positive rates, and model performance

Skills

• 5+ years of experience in a hands-on data science role, building and deploying machine learning models
• Proven experience leading complex data science projects from inception to production, including setting technical direction and guiding peers
• Expert-level Python for data analysis and modeling (pandas, scikit-learn, etc.)
• Advanced SQL skills for complex data extraction and manipulation
• Deep experience with tree-based ML models (XGBoost, CatBoost, LightGBM) and statistical models (Logistic Regression, Lasso/Ridge)
• Deep understanding of model explainability frameworks (SHAP, LIME) and algorithmic fairness to ensure models comply with credit lending regulations
• Strong understanding of sampling techniques for handling highly imbalanced datasets
• Practical experience with clustering and outlier detection techniques (e.g., K-Means, K Nearest Neighbors, Isolation Forest)
• Proven experience with the full modeling lifecycle, including model deployment, monitoring, and maintenance on a cloud platform like GCP, AWS, or Azure
• A solid foundation in statistics and experience designing and analyzing A/B tests
• Excellent stakeholder management and communication skills, with a demonstrated ability to explain complex technical concepts to diverse audiences. Advanced English level
• Direct experience in a FinTech, payments, or risk/fraud-focused role, particularly with exposure to credit or consumer lending
• Experience working with traditional credit bureau data (Experian, Equifax, TransUnion) and alternative credit/identity data sources
• Experience with Graph Neural Networks (GNNs) or graph analytics tools (e.g., Neo4j, NetworkX) to map complex fraud networks
• Familiarity with consumer lending regulations (e.g., FCRA, ECOA) and their impact on machine learning model development
• Hands-on MLOps experience (e.g., CI/CD for models, versioning, automated retraining)
• Experience with Google Cloud Platform (GCP), especially Vertex AI
• Spanish and/or Portuguese speaker

Benefits

• Competitive salary
• Initial stock options grant
• Annual performance bonus
• Health, dental, and vision plans
• Remote work environment, although we have offices in Miami and México City and would love to work in hybrid model if you are up to it.
• Continuous learning opportunities
• Unlimited PTO
• Paid parental leave
• Empowering opportunities for growth in a dynamic entrepreneurial environment

Company Overview

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