Data Scientist Senior - Fraud Model Management

The Opportunity

The Fraud Model Management Senior Data Scientist will work with senior managers and leads to implement first-line model management activities on a portfolio of fraud and financial crimes models, while closely partnering with Bank Financial Crimes leadership, Enterprise Model Risk Management (MRM), Legal, Compliance, Technology, Model Users, and other partners.

Strong candidates will be able to deploy the following work products and processes :

• Production of technical model documentation and conduct ongoing monitoring to coordinate with model partners on any performance changes
• Tracking the value and health of models with regard to loss mitigation and improvement to expense and Member experience, and use this information to prioritize deployment, retirement, upgrades and other enhancements to models
• Meeting with MRM validators and other partners to facilitate completion of MRM validation work and deliver key insights to model users on performance / strengths / weaknesses of scors
• Partnering with team leadership to ensure accuracy, completeness, and consistency of metrics in ongoing monitoring
• Production of model change logs and update model documentation
• Attends meetings with Technology and business project managers to stay abreast of upcoming projects that may affect models (changes of inputs, changes to model outputs, new / different data sources)
• Keeps model inventory current and manages attestations
• Manages model implementation testing processes
• Develops and maintains model deployment playbooks
• Manage approvals from MRM, Legal, Compliance and other governance bodies

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, 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 transparent 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.
• Manages project breakthroughs, risks, and impediments. Intensifies 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 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, supervised, 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 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
• 4 years of experience in training and validating statistical, physical, machine learning, and other sophisticated 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.
• Proven experience writing 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.
• 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.

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 : $138,230 - $248,810.

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.