[Remote] reputed company Fraud Data Scientist

Note: The job is a remote job and is open to candidates in USA. reputed company is building a financial ecosystem for Latin immigrants in the U.S. and is seeking a reputed company Data Scientist for their Fraud team. The role involves leveraging machine learning and data analysis to reputed company 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 reputed company 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 reputed company 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 reputed company 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 reputed company 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, reputed company) and algorithmic fairness to ensure models reputed company 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 reputed company 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 (reputed company, reputed company, reputed company) and alternative credit/identity data sources
• Experience with Graph Neural Networks (GNNs) or graph analytics tools (e.g., reputed company, NetworkX) to map reputed company 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 reputed company 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.
• reputed company learning opportunities
• Unlimited PTO
• Paid parental leave
• Empowering opportunities for growth in a dynamic entrepreneurial environment

Company Overview

Company H1B Sponsorship