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USAA · 6 hours ago

Senior Graph Data Scientist – Identity Analytics

San Antonio, TX

Full-time

Onsite

Senior Level

$143K/yr - $258K/yr

6+ years exp

USAA is dedicated to empowering its members to achieve financial security through competitive products and exceptional service. The Senior Graph Data Scientist – Identity Analytics will develop and implement quantitative solutions to detect and prevent identity theft and fraud, utilizing machine learning models and graph analytics.

BankingFinancial ServicesInsuranceVenture Capital

No H1B

Responsibilities

Develop and continuously update internal identity theft and authentication models to mitigate fraud losses and negative member experience from fraud application, synthetic fraud and account takeover attempts

Closely partner with Strategies team, Director of Fraud Identity Analytics and Director of Fraud Model Management and Model Users on model builds and priorities

Partner with Technology and other key collaborators to deploy a Financial Crimes graph database strategy, including vendor selection, business requirements, data needs, and clear use cases spanning financial crimes

Deploy graph databases and graph techniques to identify criminal networks engaging in fraud, scams, disputes/claims and AML and deliver highly significant benefits

Generate and prioritize fraud-dense rings to mitigate losses and improve Member experience

Identify and work with technology to integrate new data sources for models and graphs to augment predictive power and improve business performance

Exports insights to decision systems to enable better fraud targeting and model development efforts

Drives continuous innovation in modeling efforts including advanced techniques like graph neural networks

Collaborate with the broader analytics community to share standard methodologies and techniques

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 sophisticated 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 innovative 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 optimally identified, measured, supervised, and controlled in accordance with risk and compliance policies and procedures

Qualification

Predictive analyticsMachine learningGraph databasesStatistical modelingPythonSQLData analysisMentoringCommunicationDocumentation

Required

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 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

Proven experience writing code that is easy to follow, well documented, and commented where vital 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, 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, and ensemble methods such as Random Forests, XGBoost, LightGBM, and CatBoost

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