Senior Data Scientist Vice President

Senior Data Scientist Vice President at Citi focusing on analytical Solutions across lines of business using statistical and advanced analytics with emphasis on ML, predictive modeling and fraud detection to drive strategic insights.

Responsibilities

• Develop analytical solutions to minimize losses across all lines of business using statistical and advanced data science methods.
• Examine compromised card data from dark web feeds to identify emerging fraud trends, detect unusual patterns and anomalies, and pinpoint high‑risk merchants, locations, and transaction behaviors.
• Apply AI and ML models such as anomaly detection, graph neural networks, and NLP to forecast fraudulent activity.
• Utilize AI driven automation to enhance fraud detection efficiency.
• Refine data models and algorithms to flag high‑risk accounts for proactive monitoring and closure; quantify risk exposure by analyzing the impact of compromised cards on fraud losses and identifying abnormal spending patterns.
• Collaborate with threat intelligence teams to weave external fraud signals into risk models.
• Identify fraud rings, mule accounts and synthetic identities by linking compromised data to existing customer portfolios.
• Produce executive‑level insights and dashboards using advanced visualizations with regular updates on fraud trends and emerging threats; deliver actionable insights to senior global stakeholders.
• Lead proofs of concept with new vendors evaluating fraud detection tools, data enrichment platforms, and dark web monitoring solutions.
• Conduct ad hoc analyses on large unstructured datasets such as transaction logs and dark web feeds to identify fraud indicators, using Python, SQL and SAS for ETL and analysis.
• Coordinate response to significant fraud events by facilitating information sharing across financial crime and fraud prevention organizations; partner with cross‑functional teams to design intelligence‑driven solutions.
• Collaborate with fraud analytics modeling to explore new detection capabilities and develop analytical solutions leveraging unstructured data and new variables.

Requirements

• Bachelor’s degree in engineering, statistics, economics, finance, mathematics or related quantitative field from a premier institute; Master’s degree is not required but beneficial.
• 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 working knowledge of Python (preferred), SQL, SAS (SAS required).
• Experience with AI/ML frameworks such as TensorFlow, PyTorch and Scikit‑learn.
• Knowledge of Large Language Models for text analysis and Fraud Intelligence.
• Experience with 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 with cybersecurity datasets and threat intelligence platforms.
• Experience developing dynamic dashboards using Tableau or similar visualization tools.
• Data Science work in any risk domain is preferable.
• Experience identifying fraud patterns in large consumer banking portfolios.
• Proven analytic, problem solving and leadership skills with the 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 weigh risk/reward trade‑offs.
• Ability to collaborate effectively with cross‑functional partners and management.
• Solutions oriented, proactive attitude with the ability to drive innovation through thought leadership while maintaining an end‑to‑end view.
• Extremely detail oriented with intellectual curiosity; capable of multi‑tasking in a fast paced and evolving environment while upholding high standards.

Technologies

• Python
• SQL
• Teradata
• RDBMS
• Hadoop
• Hive
• SAS
• TensorFlow
• PyTorch
• Scikit-learn
• Tableau

Benefits

• Medical coverage
• Dental coverage
• Vision coverage
• 401(k) plan
• Life insurance
• Accident insurance
• Disability insurance
• Wellness programs
• Paid time off (vacation, sick leave)
• Paid holidays
• Incentive and retention awards

Location

San Antonio, Texas, United States (onsite)

Salary

USD 113,840 - 170,760 per year