Senior Data Scientist Vice President

This role is a member of the Fusion Analytics Team under FFC, tasked with creating analytical solutions across all lines of business using statistical and advanced analytical techniques to drive strategic insights and decision-making.

Responsibilities

• Create analytical solutions to mitigate losses across all LOBs using statistical and advanced data science techniques.
• Analyze compromised cards data from the dark web to identify emerging fraud trends, detect suspicious patterns and anomalies, and pinpoint high-risk merchants, locations, and transaction behaviors.
• Leverage AI/ML models (e.g., anomaly detection, graph neural networks, NLP) to anticipate fraudulent behavior.
• Implement AI-powered automation to improve fraud detection efficiency.
• Develop and enhance data models and algorithms to identify high-risk accounts for proactive monitoring and closure.
• Assess the impact of compromised cards on fraud losses, use statistical analysis to quantify risk exposure, and identify abnormal spending patterns.
• Collaborate with threat intelligence teams to incorporate external fraud signals into risk models.
• Identify fraud rings, mule accounts, and synthetic identities by linking compromised data to existing customer portfolios.
• Generate executive-level insights and reports for leadership using advanced visualization techniques, providing regular updates on fraud trends and emerging threats.
• Provide actionable insights to senior global stakeholders by leveraging data analytics and reporting.
• Serve as the lead point of contact with new vendors, evaluating fraud detection tools, data enrichment platforms, and dark web monitoring solutions.
• Perform ad-hoc analysis on large, unstructured datasets (e.g., transaction logs, dark web feeds) to identify fraud indicators using Python, SQL, and SAS.
• Manage significant fraud events by coordinating information sharing across financial crime and fraud prevention organizations.
• Partner with cross-functional teams such as Fraud Policy, Analytics & Modelling, and the Security Operations Center to design intelligence-derived solutions for fraud detection.
• Collaborate with the fraud analytics modeling function to understand new fraud detection capabilities and develop analytical solutions leveraging unstructured datasets.

Requirements

• Bachelor’s degree in Engineering, Statistics, Economics, Finance, Mathematics, or a related quantitative field from a premier institute (Master’s degree beneficial but not required).
• Minimum 5+ years of relevant experience in data analysis, data mining, or statistical analysis.
• Working knowledge of Python, SQL, Teradata, RDBMS, and Hadoop/Hive tools.
• Experience in statistical analysis with proficiency in at least one of the following: Python (preferred), SQL, or SAS (required).
• Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Knowledge of Large Language Models (LLMs) for text analysis and fraud intelligence.
• Experience in predictive modeling, statistical analysis, and machine learning techniques.
• Ability to analyze large-scale, unstructured data and generate actionable insights.
• Familiarity with digital fraud detection tools and experience working with cybersecurity datasets and threat intelligence platforms.
• Prior experience developing dynamic dashboards using visualization tools such as Tableau.
• Data science experience in any risk domain is preferable.
• Experience identifying fraud patterns in large consumer banking portfolios.

Skills

• Demonstrable analytic, problem-solving, and leadership skills.
• Ability to deliver projects in a fast-paced environment.
• Excellent quantitative and analytic skills with a data-driven mindset.
• Ability to derive patterns, trends, and insights, and perform risk/reward trade-offs.
• Strong collaboration skills with cross-functional partners and management.
• Solutions-oriented “can-do” attitude with the ability to drive innovation through thought leadership while maintaining an end-to-end view.
• Extremely detail-oriented with strong intellectual curiosity.
• Ability to effectively multi-task in a fast-paced and evolving environment while setting high standards.

Benefits

• Competitive medical, dental, and vision coverage.
• 401(k) retirement plan.
• Life, accident, and disability insurance.
• Wellness programs.
• Paid time off packages, including vacation, sick leave, and holidays.
• Discretionary and formulaic incentive and retention awards for eligible employees.

Pay

Full-time salary range: $113,840.00 - $170,760.00.

Schedule

Full time.

Primary location: San Antonio, Texas, United States.