Lead Data Scientist – Financial Crimes and Transaction Analytics

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

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, computer science, discernment, and other interpersonal skills.
• Participates in enterprise-level efforts to drive the maintenance and transformation of data science technologies and culture.
• Ensures risks associated with business activities are effectively identified, measured, monitored, 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 subject area; 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.
• 8 years of experience in a predictive analytics or data analysis
• 6 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 language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
• Expert ability to write code that is easy to follow, well documented, and commented where necessary 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.
• Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
• Proven ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
• Project management experience that demonstrates the ability to anticipate and appropriately manage project breakthroughs, risks, and impediments.
• Demonstrated history of appropriately communicating potential issues that could limit project success or implementation.
• Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic models, discriminant analysis, support vector machines, decision trees, forest models, etc.
• Expert level experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
• Demonstrated experience in guiding and mentoring junior technical staff in business interactions and model building.
• Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science.
• A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent).
• Extensive technical skills, consulting experience, and business savvy to collaborate with all levels and fields within the organization.

What sets you apart:

• US military experience through military service or a military spouse/domestic partner
• Graduate degree in a quantitative subject area
• Over 4 years of experience with model development
• Experience in fraud/financial crimes model development

The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.

What we offer:

Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. The salary range for this position is: $158,960 - $286,130.

Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.

Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include 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, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals.

For more details on our outstanding benefits, please visit our benefits page on USAAjobs.com.

Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting.

 

USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.