[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.ResponsibilitiesDefine the long-term machine learning strategy for the fraud team, establish technical best practices, and mentor junior data scientistsOwn the entire lifecycle of fraud detection models, from data exploration and feature engineering to model training, validation, deployment, and monitoringDesign and develop models specifically targeted at lending fraud typologies, including synthetic identity fraud, first-party loan default fraud, and application fraudConduct 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 ringsDesign and execute A/B tests to measure the impact of new models, rules, and strategies on both fraud detection rates and user experiencePartner 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 audiencesDeploy, monitor, and maintain machine learning models in a cloud environment, ensuring high availability and performanceBuild and maintain dashboards using tools like Tableau or Looker to track key performance indicators (KPIs) like fraud loss rates, false positive rates, and model performanceSkills5+ years of experience in a hands-on data science role, building and deploying machine learning modelsProven experience leading complex data science projects from inception to production, including setting technical direction and guiding peersExpert-level Python for data analysis and modeling (pandas, scikit-learn, etc.)Advanced SQL skills for complex data extraction and manipulationDeep 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 regulationsStrong understanding of sampling techniques for handling highly imbalanced datasetsPractical 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 AzureA solid foundation in statistics and experience designing and analyzing A/B testsExcellent stakeholder management and communication skills, with a demonstrated ability to explain complex technical concepts to diverse audiences. Advanced English levelDirect experience in a FinTech, payments, or risk/fraud-focused role, particularly with exposure to credit or consumer lendingExperience working with traditional credit bureau data (Experian, Equifax, TransUnion) and alternative credit/identity data sourcesExperience with Graph Neural Networks (GNNs) or graph analytics tools (e.g., Neo4j, NetworkX) to map complex fraud networksFamiliarity with consumer lending regulations (e.g., FCRA, ECOA) and their impact on machine learning model developmentHands-on MLOps experience (e.g., CI/CD for models, versioning, automated retraining)Experience with Google Cloud Platform (GCP), especially Vertex AISpanish and/or Portuguese speakerBenefitsCompetitive salaryInitial stock options grantAnnual performance bonusHealth, dental, and vision plansRemote 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 opportunitiesUnlimited PTOPaid parental leaveEmpowering opportunities for growth in a dynamic entrepreneurial environmentCompany OverviewFélix is ​​a chat-based platform that enables Latinos in the US to send money abroad. It was founded in 2020, and is headquartered in San Francisco, California, USA, with a workforce of 51-200 employees. Its website is https://www.felixpago.com.Company H1B SponsorshipFélix has a track record of offering H1B sponsorships, with 1 in 2026, 6 in 2025, 13 in 2024. Please note that this does not guarantee sponsorship for this specific role.