Essential Responsibilities:
- Contribute to fraud strategy development across the full credit lifecycle
- Lead the development, testing and rollout of Fraud strategies through the full credit lifecycle. This includes developing the change request, obtaining all approvals, partnering with implementation teams to implement changes, ensuring appropriate controls, and completing performance reviews. Supervise champion-challenger testing and the development, validation and implementation of decision tree segmentations
- Partner with the Credit SLT to contribute to strategic planning, resource allocation, coordination of people and resources and work prioritization
- Lead a team of professionals by providing mentorship, guidance, engagement, career pathing and development opportunities to the team. This includes hiring, training, developing, managing, coaching, and retaining team members
- Create processes and controls to ensure that data, analyses, strategies, and recommendations are accurate.
- Identify and drive adoption of best practices across team (e.g., performance monitoring / test reads).
- Build strong relationships with the leaders of the Credit Strategy teams above and create structured interaction models.
- Partner with each supported team to develop a compelling future state vision and roadmap to reach future state.
- Co-lead the identification and adoption of best-in-class methodologies, processes, and tools to enhance strategy development and analytics.
- Provide support for frequent regulatory exams, internal audits and second line of defense reviews.
Qualifications/Requirements:
- Bachelor's degree with a minimum 10+ years of fraud or risk management experience
- Experience in building fraud strategies for new acquisition, transactions fraud using new and alternative data and algorithms
- Proven ability to derive actionable credit and fraud insights from data and a solid foundation in advanced analytical and modeling methodologies
- Strong relationship building, communication (verbal, written) and influencing skills; must be able to communicate with and influence executives.
- Experience and understanding of advanced analytical tools such as SAS, Python, Spark, SQL, Advanced EXCEL (macro/pivots/power query etc.) or other equivalent coding languages
Desired Characteristics:
- Master's degree in any quantitative field
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