Lead Data Scientist / Gen AI Lead

TIAA is seeking a Lead Data Scientist to join our Enterprise Fraud Management team. The individual will work on designing, implementing, and evaluating models that detect fraud across a variety of channels. You will also contribute to exploratory projects involving generative AI (e.g., synthetic data generation, anomaly scenario simulation, language modeling for fraud detection insights). This is a hands-on role for someone looking to grow in both classical data science and emerging AI technologies.

Key Responsibilities and Duties

• Develop and maintain fraud detection models using supervised and unsupervised learning techniques (e.g., random forests, XGBoost, isolation forests, Clustering Techniques).
• Partner with engineers and analysts to deploy models in production and monitor their performance.
• Perform data wrangling, feature engineering, and exploratory data analysis (EDA) on large-scale transactional and behavioral data.
• Collaborate cross-functionally with product, risk, and engineering teams to understand fraud patterns and improve detection coverage.
• Assist in the development of dashboards and visualizations for communicating model insights to stakeholders.
• Use generative AI (e.g., LLMs) to support advanced analytics projects such as:
  • Generating synthetic fraud scenarios
  • Automating risk report generation
  • Detecting or interpreting anomalies in textual/behavioral data

Educational Requirements

• University (Degree) Preferred

Work Experience

• 5+ Years Required; 7+ Years Preferred

Physical Requirements

• Physical Requirements: Sedentary Work

Career Level
8IC

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