Data Scientist-Vice President

JPMorgan Chase & Co.; Plano (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Data Scientist Vice President to join the Fraud Strategy team. You will shape fraud risk strategies using advanced analytics and cross-functional collaboration to protect the business, customers, and communities.

You will lead complex projects, drive strategic conversations with stakeholders, and deliver impactful solutions that mitigate fraud risks while supporting data-driven decision making at the executive level.

Qualifications

• Minimum 5 years in Fraud Strategy, analytics, or a quantitative discipline.
• Ability to lead complex projects independently and manage multiple priorities.
• Experience driving conversations and building consensus across functions.
• Excellent analytical and problem-solving skills with attention to detail.
• Exceptional written and verbal communication; able to present analyses to executives.
• Strong background in statistics, econometrics, or related quantitative methods.
• Bachelor’s degree in a finance/economics/statistics or quantitative field.
• Advanced proficiency in SAS, SQL, and spreadsheet tools; query large datasets for insights.

Responsibilities

• Lead analytics development to provide insights into fraud trends and account quality.
• Oversee metrics analysis and profitability drivers across the account lifecycle.
• Understand operational processes to identify fraud risk drivers.
• Direct and execute complex projects from analysis to implementation and monitoring.
• Foster collaboration with stakeholders and represent Fraud Strategy in cross-functional initiatives.
• Communicate findings and recommendations clearly to executive leadership.

Skills

Fraud analytics

Project leadership

Stakeholder management

Analytical thinking

Communication

Statistics/Econometrics

SQL & SAS

Education

Bachelor's degree in finance/economics/statistics

Tools

SAS

SQL

Excel

Job description

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.

Job Responsibilities

• 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.

Required Qualifications, Capabilities, and Skills

• 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.