Investment Data Scientist - Senior

USAA • Chesapeake, VA

2d • Hybrid

About The Position

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 As a dedicated Investment Data Scientist - Senior, you will work with the Data Science Team in USAA’s Finance department. Their responsibilities will include working with investment risk models (Valuation, Performance Attribution, VaR, CECL), investment data management, external asset manager relations, and investment operational risk & processes. Additionally, they will support USAA’s Chief Investment Office with investment analysis. 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. 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.

Requirements

• 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.
• 6 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 4 years of experience in predictive analytics or data analysis.
• 4 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.
• Validated experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code visibility).
• 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.
• Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
• Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
• Advanced 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.
• Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors’ algorithms, DBSCAN, etc.
• Experience guiding and mentoring junior technical staff in business interactions and model building.
• Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results.

Nice To Haves

• MS in Financial Engineering
• 5+ Years of Investment Modeling & Operations Experience
• Experience with Aladdin BlackRock
• Experience with Investment Data Analytics
• Strong knowledge of Python, Snowflake, SQL, Dashboard Reporting

Responsibilities

• 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, and assists peers with composing, 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.
• Works with business and analytics leaders to prioritize analytics and modeling problems/research efforts.
• Builds and maintains a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are visible and based on the highest quality data.
• Translates complex 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.
• Handles project landmarks, risks, and impediments. Calls out potential issues that could limit project success or implementation.
• Develops standard methodologies for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling procedures and model risk management standards.
• Maintains expertise and awareness of pioneering techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
• Serves as a mentor to junior data scientists in modeling, analytics, and computer science tasks.
• Participates in internal communities that 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.

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, visit our benefits page on USAAjobs.com.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level