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