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

We are an Equal Opportunity Employer. TIAA does not discriminate against any candidate or employee on the basis of age, race, color, national origin, sex, religion, veteran status, disability, sexual orientation, gender identity, or any other legally protected status.

Read more about your rights and view government notices .

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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

We are an Equal Opportunity Employer. TIAA does not discriminate against any candidate or employee on the basis of age, race, color, national origin, sex, religion, veteran status, disability, sexual orientation, gender identity, or any other legally protected status.

Read more about your rights and view government notices .

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.