Data Science Lead- Fraud Modeling

Citizens • Columbus, OH

2h

About The Position

Citizens Bank is seeking a Data Science Lead to spearhead enterprise fraud modeling initiatives. This role combines hands-on technical expertise with leadership responsibilities, driving innovation and ensuring high-quality model development in a regulated environment.

Requirements

• 5+ years of experience in fraud modeling or strategy
• Demonstrated ability to lead teams and mentor junior colleagues
• Strong communication skills, including presentations and deck creation
• Experience engaging with model risk governance in a regulated institution
• Expertise in handling large-scale datasets and real-time time series modeling
• Hands-on experience building machine learning and deep learning models for fraud detection
• Cloud Experience (AWS): At least 5 years’ experience
• Python or SAS: Expert level
• SQL: Expert Level
• PySpark: Intermediate to Expert
• GitHub / BitBucket: Intermediate to Expert
• Master’s degree in one of the above fields (Minimum)

Nice To Haves

• Neo4J: Preferred
• Apache Flink: Nice to have
• Ph.D. in Engineering, Statistics, Computer Science, Data Science, Mathematics, or Operations Research (Preferred)

Responsibilities

• Lead the design, planning, and development of fraud detection ML models
• Supervise and mentor a team of data scientists & data analysts, fostering technical growth and collaboration
• Act as a thought leader, introducing new methodologies and technologies to enhance modeling capabilities
• Participate in hands-on coding and modeling activities
• Maintain a well-organized, high-quality codebase—and enforce best practices in version control
• Contribute to strategic visioning and translate plans into actionable steps for the team
• Engage with stakeholders to provide consultative insights and regular progress updates
• Build and maintain business relationships with data engineering and fraud strategy teams
• Maintain project timelines and deliverables

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level