Why USAA?
Let’s do something that really matters.
At USAA, we have an important mission: facilitating the financial security of millions of U.S. military members and their families. Not all our employees served in our nation’s military, but we all share in the mission to give back to those who did. We’re working as one to build a great experience and make a real impact for our members.
We believe in our core values of honesty, integrity, loyalty, and service. They’re what guides everything we do – from how we treat our members to how we treat each other. Come be a part of what makes us so special!
As a dedicated Lead Data Scientist, you will translate business problems into applied statistical, machine learning, simulation, and optimization solutions to advise actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. In collaboration with engineering partners, delivers solutions at scale, and enables customer-facing applications. Leverages' database, cloud, and programming knowledge to build analytical modeling solutions using statistical and machine learning techniques. Collaborates with other data scientists to improve USAA’s tooling, expanding the company’s library of internal packages and applications. Works with model risk management to validate the results and stability of models before being pushed to production at scale.
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, Chesapeake, VA 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.
The Opportunity
Responsibilities
The Lead Data Scientist – Financial Crimes and Transaction Analytics is 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
• Develops and mentors more junior members of the organization and collaborates with the broader analytics community to share standard methodologies and techniques
What You'll Do
• Gathers, interprets, and manipulates complex structured and unstructured data to enable advanced analytical solutions for the business.
• Leads and conducts advanced analytics demonstrating machine learning, simulation, and optimization to deliver business insights and achieve business objectives.
• Guides team on selecting 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 and peer reviews technical documents for knowledge persistence, risk management, and technical review audiences.
• Partners with business leaders from across the organization to proactively identify business needs and proposes/recommends analytical and modeling projects to generate business value.
• Works with business and analytics leaders to prioritize analytics and highly complex modeling. problems/research efforts.
• Leads efforts to build and maintain 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.
• Assists team with translating business request(s) into specific analytical questions, implementing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations.
• Manages project portfolio breakthroughs, risks, and impediments. Anticipates potential issues that could limit project success or implementation and intensifies as needed.
• Establishes and maintains standard methodologies for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards.
• Interacts with internal and external peers and management to maintain expertise and awareness of innovative techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
• Serves as a mentor to data scientists in modeling, analytics,
Location: Charlotte, NC
Posted: Oct. 21, 2024, 9:23 p.m.
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