Back
Senior role at a well-funded fintech in a metro with desirable ML/AI skills, moderate competition.
Fraud and risk-specific ML expertise and production GenAI focus reduce cross-industry transferability.
Explicit 10+ years, deep fraud ML expertise and production GenAI requirements create stringent filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and develop advanced predictive machine learning models for global fraud detection, risk assessment, and anomaly detection with a focus on highly imbalanced data.
Build, implement, and scale production-grade GenAI and Agentic AI workflows to automate fraud alert handling and accelerate investigations.
Serve as the Subject Matter Expert driving technical standards, collaborating across teams to deploy models, monitor data/model drift, and improve feature engineering and model performance metrics.
10+ years of experience in Data Science or Machine Learning with significant fraud or risk mitigation focus in a fast-paced environment.
Expertise in classical ML algorithms (e.g., XGBoost, LightGBM, Random Forests, SVMs) and statistical modeling.
Hands-on experience in production deployment of GenAI and Agentic AI workflows using platforms like AWS or GCP.
Proficiency in Python (including PyTorch, Hugging Face), SQL, big-data technologies (e.g., Spark, Hadoop), and cloud platforms (AWS or GCP).
Experienced technical Individual Contributor comfortable leading by example and driving production ML systems end-to-end in fraud and risk domains.
Deep theoretical and practical expertise in handling highly imbalanced datasets and continuous monitoring/mitigation of data and concept drift.
Demonstrated technical eminence through research contributions, patents, or open-source projects in fraud or ML applications.