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About The Role As a Lead Data Scientist for our Fraud team, you will be on the front lines of protecting our company and our customers. You will leverage your expertise in machine learning, statistics, and data analysis to design, build, and deploy sophisticated models that detect and prevent fraudulent activity in real‑time. This high‑impact role will translate your work directly into protecting millions of dollars and ensuring a trustworthy platform for our users.
Responsibilities
Technical Leadership & Strategy: Define the long‑term machine learning strategy for the fraud team, establish technical best practices, and mentor junior data scientists.
End‑to‑End Model Development: Own the entire lifecycle of fraud detection models, from data exploration and feature engineering to model training, validation, deployment, and monitoring.
Credit & Lending Fraud Mitigation: Design and develop models for lending fraud typologies, including synthetic identity fraud, first‑party loan default fraud, and application fraud.
Advanced Analysis: 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.
Experimentation: Design and execute A/B tests to measure the impact of new models, rules, and strategies on fraud detection rates and user experience.
Stakeholder Collaboration: Partner with Product, Engineering, Risk, and Operations to translate business needs into data science solutions, integrate ML scores with rule engines, and communicate results to non‑technical audiences.
Productionalize Models: Deploy, monitor, and maintain machine learning models in a cloud environment,



ensuring high availability and performance.
Reporting & Visualization: Build and maintain dashboards using tools such as Tableau or Looker to track key performance indicators (KPIs) like fraud loss rates, false positive rates, and model performance.
Requirements
Must‑Haves:
5+ years in a data science role building and deploying machine learning models.
Leadership: Proven experience leading complex data science projects and guiding peers.
Python: Expert‑level Python for data analysis and modeling (pandas, scikit‑learn, etc.).
SQL : Advanced SQL skills for complex data extraction and manipulation.
Machine Learning Modeling: Deep experience with tree‑based ML models (XGBoost, Cat Boost, LightGBM) and statistical models (Logistic Regression, Lasso/Ridge).
Model Explainability & Ethics: Knowledge of explainability frameworks (SHAP, LIME) and algorithmic fairness for compliance with credit lending regulations.
Sampling Techniques: Understanding of sampling techniques for highly imbalanced datasets.
Unsupervised Learning: Practical experience with clustering and outlier detection (K‑Means, K‑Nearest Neighbors, Isolation Forest).
Model Lifecycle & Cloud: Experience with full lifecycle, deployment, monitoring, and maintenance on GCP, AWS, or Azure.
Analytical Rigor:



Solid foundation in statistics and experience designing and analysing A/B tests.
Communication: Excellent stakeholder management and communication skills; ability to explain complex concepts to diverse audiences. Advanced English required.
Equivalent competencies will be considered.
Nice to have
Domain Experience in Fin Tech, payments, or risk/fraud‑focused roles, especially credit or consumer lending.
Alternative & Bureau Data experience with Experian, Equifax, Trans Union, or alternative credit/identity data sources.
Graph ML: Experience with Graph Neural Networks (GNNs) or graph analytics tools (Neo4j, NetworkX).
Regulatory Familiarity: Knowledge of consumer lending regulations (FCRA, ECOA) and impact on ML models.
MLOps: Hands‑on experience with CI/CD, versioning, automated retraining for models.
GCP / Vertex AI: Experience using Vertex AI on Google Cloud Platform.
Spanish and/or Portuguese speaker.
What We Offer
Competitive salary
Initial stock options grant
Annual performance bonus
Health, dental, and vision plans
Remote work environment with hybrid options from offices in Miami and Mexico City
Continuous learning opportunities
Unlimited PTO
Paid parental leave
Opportunities for growth in a dynamic entrepreneurial environment
Equal Opportunity Employer At Félix, we are committed to providing equal employment opportunities to all qualified employees and applicants without regard to race, religion, nationality, sex, sexual orientation, gender identity, age, or disability. This policy applies to all terms and conditions of employment, including recruitment, hiring, placement, promotion, training, compensation, benefits, and termination.
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Postúlate en Kit Empleo: kitempleo.com.ar/empleo/q5b72

📌 Lead Fraud Data Scientist (Argentina)
🏢 Felix
📍 Argentina