Why USAA?
At USAA, we have an important mission: facilitating the financial security of millions of U.S. military members and their families. Not all of 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!
The Opportunity
The Enterprise financial risk management stress testing oversight team is looking for a data scientist I, this person will be translates business problems into applied statistical, machine learning, simulation, and optimization solutions to inform 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.
The data scientist I position is a hybrid work type and can be based in one of the following locations: Plano, TX or San Antonio, TX; Hybrid roles help employees gain the best of both worlds – collaborating in-person in the office and working from home when needed to achieve focused results
What you’ll do:
- Gathers, interprets, and manipulates structured and unstructured data to enable advanced 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, executes on 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 stakeholders 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 cutting-edge techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
- 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; OR 4 years of 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 discipline 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 advanced analytics models.
- 2 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.
- Experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).
- Experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
- 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.
- Experience in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
- Ability to assess regulatory implications and expectations of distinct modeling efforts.
- 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.
- Experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
- Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results.
What sets you apart:
- Knowledge of and interest in exploring relationships between macroeconomic variables and impact to financial institutions
- Ability to create insightful visualizations of complex data and communicate findings to senior executives and broad audiences
- Experience with developing models/assumptions used in FP&A, Stress Testing, or CECL
- Experience in financial risk management
- Experience in consumer loan and credit card revenue forecast and origination forecast
- Experience with Python, R, Tableau, Essbase, SAS preferred
- Work experience in large financial institutions
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: $95,250 – $182,030.
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.
Relocation assistance is not available for this position.
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.