Senior Data Scientist Financial Crimes and Transaction Analytics

$138,230 - $248,810/Yr

USAA - Chesapeake, VA

Full-time - Senior

Remote - Chesapeake, VA

10,001+ employees

Credit Intermediation and Related Activities

About the position

As a dedicated Senior Data Scientist at USAA, you will play a crucial role in translating complex business problems into actionable insights through the application of statistical methods, machine learning, simulation, and optimization techniques. Your primary focus will be on developing and enhancing machine learning models that improve USAA's capabilities in detecting and preventing fraud across various financial transactions, including credit and debit card activities, checks, deposits, and digital payments. You will collaborate closely with engineering partners to deliver scalable solutions that not only drive business value but also enhance the overall member experience. This position requires a strong foundation in database management, cloud technologies, and programming, enabling you to build robust analytical modeling solutions that leverage advanced statistical and machine learning techniques. In this role, you will be responsible for gathering, interpreting, and manipulating both structured and unstructured data to enable advanced analytical solutions. You will develop scalable, automated solutions that deliver significant business insights and value, selecting appropriate modeling techniques based on data limitations and business needs. Your work will involve deploying models within the Model Development Control (MDC) and Model Risk Management (MRM) frameworks, ensuring that all models are validated and stable before being pushed to production. You will also be expected to maintain a library of reusable algorithms and supporting code, ensuring transparency and high-quality data in all model development efforts. As a mentor to junior data scientists, you will guide them in modeling, analytics, and computer science tasks, while also participating in internal communities that promote the evolution of data science technologies and culture within USAA. Your expertise will be vital in identifying and managing risks associated with business activities, ensuring compliance with risk management policies and procedures.

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.
• Translates complex business request(s) into specific analytical questions, completes the analysis and/or modeling, and communicates outcomes to non-technical business colleagues.
• Manages project breakthroughs, risks, and impediments, intensifying 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 best practices and model risk management standards.
• Maintains expertise and awareness of innovative techniques, actively seeking opportunities to learn new 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 optimally identified, measured, monitored, and controlled.

Requirements

• Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience may be substituted in lieu of degree.
• 6 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 languages (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
• Proven experience writing code that is easy to follow, well documented, and commented where necessary to explain logic.
• 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

• 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

Benefits

• 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
• Various wellness programs
• Career path planning and continuing education assistance