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Data Scientist Senior - Fraud Identity Analytics

Salary

$138.23k - $248.81k

Min Experience

6 years

Location

San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, Tampa, FL

JobType

full-time

About the job

Info This job is sourced from a job board

About the role

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 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, or Tampa, FL. Relocation assistance is not available for this position. The Senior Data Scientist - Fraud Identity Analytics is responsible for development and implementation of quantitative solutions that improve USAA's ability to detect and prevent identity theft, account takeover, and first party/synthetic fraud. These solutions will range from the development of machine learning models to broad implementation of solutions such as graph analytics to protect USAA and our Members from risks emanating from these threats. Strong candidates will be able to deploy the following work products and processes: 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 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 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.

About the company

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.

Skills

machine learning
python
r
sql
data analysis
data science
statistics
fraud detection
graph analytics