Senior Data Scientist, AI Fraud Applications

Quick Facts

• Role: Expert Data Scientist (individual contributor) focused on AI fraud applications
• Team fit: Collaborate across Analytics, Product, and Engineering

Description

Develop analytics and AI solutions for financial services, e-commerce, and other data-rich digital businesses. Translate ambiguous business problems into hypotheses, experiments, models, and prototypes, then evaluate the approaches with a focus on quality, reliability, value, and operational practicality. Stay current with generative and agentic AI and assess where it can solve business problems.

Responsibilities

• Apply advanced statistical, machine-learning, and analytical techniques to complex business problems
• Translate ambiguous business problems into structured hypotheses, experiments, models, and prototypes
• Identify new opportunities where data science and new AI technologies can create value
• Shape data strategy by identifying required data, derived features, and data assets for experimentation and scalable solutions
• Prototype and evaluate new approaches, compare with existing methods, and identify strengths and failure modes
• Develop evaluation criteria for model/solution quality, reliability, value, operational practicality, and risk
• Partner with Product, Engineering, and business teams to move concepts into practical applications
• Stay current with new technologies, including generative and agentic AI
• Share insights and mentor junior team members to build a culture of experimentation and learning

Requirements

• Master’s degree in a relevant quantitative field (Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics) or equivalent experience
• 5+ years of senior-level professional experience in data science, machine learning, statistical modeling, or advanced analytics
• Hands-on programming experience with Python and SQL
• Experience developing and evaluating statistical or machine-learning solutions using large datasets
• Experience translating business problems into analytical solutions, models, proofs of concept, or prototypes
• Experience in financial services, e-commerce, fraud, identity, credit risk, decisioning, or other data-intensive digital environments
• Experience building prototypes/analytical tools or new capabilities beyond traditional model development
• Exposure to generative AI, LLMs, AI agents, or other new AI technologies
• Experience with modern cloud analytics platforms

Benefits

• Compensation package with a bonus plan
• Medical, dental, vision, and matching 401K
• Flexible work environment (remote, hybrid, or in-office)
• Flexible time off including volunteer time off, vacation, sick time, and 12 paid holidays