Lead Data Scientist​/Gen AI Lead

Lead Data Scientist

TIAA is seeking a Lead Data Scientist to join our Fraud Data Analytics and AI Strategy team. In this role, you will sit at the intersection of advanced analytics, generative AI development and fraud prevention & detection, working to protect our customers and the institution from ever evolving fraud threats. You will be responsible for deep-dive analysis of fraud data, evaluation and optimization of existing fraud prevention and detection systems, and the development of innovative analytical and generative / agentic AI solutions on the latest technologies.

The ideal candidate is a fast learner who thrives in a collaborative environment, can translate complex data findings into actionable business recommendations, and is eager to explore frontiers of agentic and generative AI applications in financial services. You will work closely with fraud operations and technology teams, serving as an analytical bridge between business strategy and technical execution.

Key Responsibilities and Duties

• Analyze large, complex fraud datasets to identify patterns, trends, and anomalies that inform detection strategies and business decisions
• Evaluate existing static, rule-based fraud detection systems through data-driven assessments of their performance and coverage, and deliver clear, prioritized recommendations for rule updates, retirement, or new rule creation
• Partner with fraud operations teams to understand frontline detection challenges and translate operational insights into analytical hypotheses and actionable solutions
• Utilize AI-assisted development tools such as Amazon Q and Kiro to accelerate analytical workflows and solution delivery
• Prototype and contribute to the development of agentic AI applications leveraging AWS Agent Core and generative AI solutions that advance the team's fraud strategy capabilities
• Collaborate with fraud technology teams to ensure models, rules, and AI-driven outputs are implemented accurately and monitored effectively within the AWS production environment
• Design, build, and validate machine learning and statistical models to enhance fraud detection capabilities, improve precision and recall, and reduce false positive rates
• Monitor deployed models and fraud rules on an ongoing basis, identifying performance degradation or emerging detection gaps that require intervention
• Communicate findings, model results, and strategic recommendations clearly to both technical and non-technical stakeholders
• Stay current with emerging trends in fraud typologies, financial crime, and AI and machine learning developments within the AWS ecosystem, and bring relevant innovations back to the team

Educational Requirements

• University (Degree) Preferred

Work Experience

• 5+ Years Required; 7+ Years Preferred

Physical Requirements

• Physical Requirements:
  
  Sedentary Work

Career Level 8IC

Required Skills:

• 5+ years of hands-on experience in data science, analytics, or a closely related quantitative discipline
• Strong proficiency in Python or R for statistical analysis and model development
• Solid command of SQL and experience working with large-scale structured and unstructured datasets
• Demonstrated expertise in statistical modeling and machine learning techniques including classification, regression, clustering, and anomaly detection
• Ability to manage relationships across multiple stakeholder groups including operations and technology teams
• Proven ability to learn new domains, tools, and methodologies quickly and independently
• Solid understanding of model evaluation metrics for imbalanced classification problems (e.g., precision, recall, AUC, F1)

Preferred

Skills:

• Familiarity with Model Risk Management frameworks and model documentation standards in a regulated financial services environment is a plus
• Familiarity with agentic AI frameworks with exposure to AWS Agent Core being a strong advantage
• Experience in financial services, fraud detection, or financial crime analytics is a strong plus
• Experience with AI-assisted development tools such as Amazon Q and Kiro is a plus

Related

Skills:

Business Acumen, Data Preprocessing, Data Science, Innovation, Machine Learning (ML), Market/Industry Dynamics, Predictive Modeling, Programming, Statistics

Anticipated Posting End Date:

Base Pay Range: $118,000/yr - $149,000/yr

Company Overview

Every worker deserves a secure retirement. For more than 100 years, TIAA has delivered it for millions of people. Founded to help educators retire with dignity, today we're a market-leading retirement company fueled by world-class asset management. But we're not just another legacy financial services firm. We're fighting harder than ever before for our clients and the many Americans who need us.

Our Culture of Impact

At TIAA, we're on a mission to build on our 100+ year legacy of delivering for our clients while evolving to meet tomorrow's challenges. We equip our associates with future-focused skills and AI tools that enable us to advance our mission. Together, we are fighting to ensure a more secure financial…