Data Scientist I - Fraud

Why USAA?

At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families.

Embrace a fulfilling career at USAA, where our core values – honesty, integrity, loyalty and service – define how we treat each other and our members. Be part of what truly makes us special and impactful.

The Opportunity

The Data Scientist I for Fraud you will be responsible the development of machine learning models that improve USAA’s ability to detect and prevent fraud on credit card, debit card, check, deposit, digital payments, as well as in other areas such as claims and disputes. Strong candidates will be able to deploy the following work products and processes:

• Develop and continuously update internal fraud models in the transactions and payment space, demonstrating techniques ranging from statistics to highly complex AI/ML techniques, to generate highly significant reduction in fraud losses and improvement in Member experience
• Work with Strategies and Model Management teams to understand and plan model needs
• Drives continuous innovation in modeling efforts
• Collaborate with the broader analytics community to share standard methodologies and techniques

We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL.

Relocation assistance is not available for this position.

This position can work remotely in the continental U.S. with occasional business travel.

What you'll do:

• Captures, interprets, and manipulates structured and unstructured data to enable sophisticated analytical solutions for the business.
• Develops scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value.
• Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.
• Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.
• Composes technical documents for knowledge persistence, risk management, and technical review audiences.
• Assesses business needs to propose/recommend analytical and modeling projects to add business value. Participates in the prioritization of analytics and modeling problems/research efforts with business and analytics leaders.
• Contributes to the development of a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are transparent and based on the highest quality data.
• Translates business request(s) into specific analytical questions, completes the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations.
• Works closely with Data Engineering, IT, the business, and other internal partners to deploy production-ready analytical assets that are aligned with the customer’s vision and specifications while being consistent with modeling best practices and model risk management standards.
• Maintains awareness of ground breaking techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
• Ensures risks associated with business activities are optimally identified, measured, supervised, and controlled in accordance with risk and compliance policies and procedures.

What you have:

• 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 (in addition to the minimum years of experience required) may be substituted in lieu of degree.
• 4 years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master’s, PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative subject area and 2 years of experience in predictive analytics or data analysis.
• 2 years of experience in training and validating statistical, physical, machine learning, and other sophisticated analytics models.
• 2 years of experience in one or more multifaceted scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
• Experience writing cod