Hybrid Senior Data Scientist – Fraud Identity Analytics

at USAA

• Job title: Senior Data Scientist – Fraud Identity Analytics
• Job type: Full Time
• Experience level: Senior
• Salary: $138,230 - $248,810 per year
• Degree requirement: Bachelor's Degree
• Tech skills: NoSQL, Python, SQL
• Location requirements: Hybrid, San Antonio, United States

About the role

• Senior Data Scientist responsible for developing quantitative solutions to prevent fraud at USAA. Collaborating with teams to enhance fraud detection through advanced analytical techniques.

Responsibilities

• Develop and implement quantitative solutions to improve ability to detect and prevent identity theft, account takeover, and fraud
• Develop and continuously update internal identity theft and authentication models to mitigate fraud losses
• Closely partner with Strategies team, Director of Fraud Identity Analytics and Director of Fraud Model Management on model builds
• Partner with Technology to deploy a Financial Crimes graph database strategy, including vendor selection
• Deploy graph databases and graph techniques to identify criminal networks engaging in fraud
• Generate and prioritize fraud-dense rings to mitigate losses and improve Member experience
• Identify and work with technology to integrate new data sources for models and graphs
• Export insights to decision systems to enable better fraud targeting
• Drive continuous innovation in modeling efforts including advanced techniques like graph neural networks
• Collaborate with the analytics community to share standard methodologies

Requirements

• Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative field; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience may be substituted in lieu of degree.
• 6 years of experience in a predictive analytics or data analysis
• 4 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models.
• 4 years of experience in one or more dynamic scripted languages (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
• Proven experience writing code that is easy to follow, well documented, and commented where vital to explain logic (high code transparency).
• Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
• Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.
• Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
• Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
• Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc.
• Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
• Experience guiding and mentoring junior technical staff in business interactions and model building.
• Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results.

Benefits

• comprehensive medical, dental and vision plans
• 401(k)
• pension
• life insurance
• parental benefits
• adoption assistance
• paid time off program with paid holidays plus 16 paid volunteer hours
• various wellness programs
• career path planning and continuing education assistance