As a Data Scientist Vice President within the Fraud Strategy team, you will shape and execute fraud risk strategies, leveraging advanced analytics and cross-functional collaboration to protect our business, customers, and communities. You will lead complex projects, drive strategic conversations with stakeholders across multiple functions, and deliver impactful solutions that mitigate fraud risks.
- Lead the development, implementation, and enhancement of analytics to provide senior management with comprehensive insights into fraud trends and account quality.
- Oversee analysis of key performance metrics and profitability drivers across the full account lifecycle, delivering actionable recommendations to inform strategy and operational decisions.
- Gain a deep understanding of operational processes (e.g., underwriting, portfolio management, collections) to identify and address fraud risk drivers.
- Direct and execute complex projects from initial analysis through implementation and performance monitoring, ensuring alignment with organizational objectives.
- Drive strategic conversations and foster collaboration with stakeholders across various functions, representing the Fraud Strategy team in cross-functional initiatives.
- Communicate findings and recommendations clearly to executive leadership and stakeholders, supporting data-driven decision making.
- Minimum 5 years of experience in Fraud Strategy, analytics, or a quantitative discipline.
- Demonstrated ability to lead complex projects independently, manage multiple priorities, and deliver results.
- Experience driving conversations and building consensus across multiple functions.
- Excellent analytical and problem-solving skills, with a keen attention to detail.
- Exceptional written and verbal communication skills; proven ability to present complex analyses and recommendations to executive management and stakeholders.
- Strong background in statistics, econometrics, or related quantitative methodologies.
- Bachelor’s degree in finance, economics, statistics, or a quantitative field.
- Advanced proficiency in SAS, SQL, and spreadsheet tools; ability to query and manipulate large datasets to generate actionable insights.