Location Plano, Texas

Job ID

R0093521

Date posted

10/27/2023

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 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

As a dedicated Data Scientist Lead-Market Risk Quant, you may work from one of our regional offices: San Antonio, TX, Plano, TX, Phoenix, AZ, Tampa, FL, Colorado Springs, CO, Charlotte, NC or work remotely in the continental U.S. with occasional Business travel.

This position will report to the Director - Quantitative Risk Management, Enterprise Market Risk within the second line of defense ERM team. In this role, the Lead Data Scientist will build predictive machine learning (ML) models which will be used to challenge first line capital market assumptions (CMAs) that drive strategic asset allocation decisions. Typical responsibilities will include data gathering / wrangling / exploratory data analysis, feature extraction / engineering, fitting the model to an appropriate ML algorithm, and evaluating model performance. Additionally, this role will be responsible for documentation requirements to aid in internal model validation. The initial focus will be on forecasting interest rates and equity market returns, but that scope may broaden over time.

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 using 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 clear and based on the highest quality data.
• Assists team with translating business request(s) into specific analytical questions, performing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations.
• Manages project portfolio achievements, risks, and impediments. Anticipates potential issues that could limit project success or implementation and advances as needed.
• Establishes and maintains standard processes 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 groundbreaking 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 (12 years total experience).
• 8 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 field and 6 years of experience in predictive analytics or data analysis.
• 6 years proven experience in training and validating machine learning, statistical, physical, and other advanced analytics models.
• 4 years of demonstrated ability in one or more dynamic scripted language (such as Python) for performing statistical analyses and/or building and scoring AI/ML models.
• Experienced 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, etc.
• Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
• Validated ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
• Project management experience that demonstrates the ability to anticipate and appropriately handle project achievements, risks, and impediments.
• 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.
• Advanced level of 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.
• Proven 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 consistent 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 subject areas within the organization.

What sets you apart:

• Experience working as a quantitative strategist / researcher or risk manager for a hedge fund.
• Strong knowledge of one or more of the following asset classes: equities, commercial real estate, fixed income.
• Experience in working with time series financial markets and economic data.
• Proficiency in python (NumPy, pandas, scikit-learn), SQL, Excel, and data visualization.
• Basics of object-oriented programming and ability to write scalable, maintainable code.
• Strong machine learning capabilities (classification and regression models, supervised and unsupervised learning, feature extraction and engineering, model regularization and Hyper-parameter tuning, cross-validation, model performance evaluation).

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: $152,290 - $291,040.

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.

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