Lead Graph Data Scientist - Identity Analytics

Salary: $164,780 - 314,960 per year Requirements:

• We require a bachelors degree in mathematics, computer science, statistics, economics, finance, actuarial science, science and engineering, or another closely related quantitative discipline, or 4 additional years of relevant statistical, mathematical, or quantitative analytics experience in lieu of a degree.
• We require 8 years of experience in predictive analytics or data analysis.
• We require 6 years of experience training and validating statistical, physical, machine learning, or other advanced analytics models.
• We require 4 years of experience using dynamic scripting languages such as Python or R for statistical analysis and/or building and scoring AI/ML models.
• We require expert-level ability to write clear, well-documented, and commented code with strong transparency.
• We require strong experience querying and preparing data from structured and/or unstructured databases using SQL, NoSQL, or similar query languages.
• We require strong experience working with structured, semi-structured, and unstructured data sources such as delimited files, JSON/XML, text, images, and related formats.
• We require excellent demonstrated skill in ad hoc analytics using descriptive, diagnostic, and inferential statistics.
• We require proven ability to assess and explain regulatory implications and expectations related to different modeling efforts.
• We require project management experience showing the ability to anticipate and manage milestones, risks, and blockers, along with strong communication of issues that may affect project success or implementation.
• We require expert-level experience with classical supervised modeling techniques such as linear/logistic models, discriminant analysis, support vector machines, decision trees, and ensemble methods including Random Forest, XGBoost, LightGBM, and CatBoost.
• We require expert-level experience with unsupervised modeling techniques such as k-means clustering, hierarchical/agglomerative clustering, nearest-neighbors methods, and DBSCAN.
• We require demonstrated experience mentoring junior technical staff in business interactions and model development.
• We require the ability to communicate highly technical ideas to teammates and business leaders who may have limited technical background.
• We require a strong track record of presenting results, insights, and technical solutions to senior executive leadership or equivalent.
• We require extensive technical skill, consulting experience, and business acumen to collaborate across all levels and functions of the organization.

• We develop and continually refine internal identity theft and authentication models to reduce fraud losses and lessen negative member impact from fraudulent applications, synthetic fraud, and account takeover attempts.
• We partner closely with strategy, fraud identity analytics, fraud model management, and model users on model development and prioritization.
• We work with Technology and other stakeholders to deliver a Member Protection graph technology strategy, including vendor selection, business requirements, data needs, and use cases across financial crimes.
• We deploy graph databases and graph methods to uncover criminal networks involved in fraud, scams, disputes/claims, and AML, improving detection and loss mitigation.
• We identify and prioritize fraud-dense rings to reduce losses and enhance the member experience.
• We collaborate on integrating new data sources for models and graphs to strengthen predictive performance and business outcomes.
• We export insights into decision systems to improve fraud targeting and model development.
• We drive ongoing innovation in modeling, including advanced approaches such as graph neural networks.
• We develop and mentor junior staff while fostering a research-and-development culture alongside day-to-day work.
• We gather, interpret, and manipulate complex structured and unstructured data to support advanced analytical solutions.
• We lead sophisticated analytics using machine learning, simulation, and optimization to generate insights and support business goals.
• We help select suitable modeling techniques and technologies based on data constraints, application needs, and business objectives.
• We develop and deploy models within the Model Development Control and Model Risk Management frameworks.
• We draft and peer review technical documentation for knowledge retention, risk control, and technical audiences.
• We partner with business leaders to identify needs and recommend analytical and modeling initiatives that create business value.
• We collaborate with business and analytics leaders to prioritize advanced modeling problems and research efforts.
• We build and maintain reusable, production-ready algorithms and code libraries that support transparent, high-quality model development and research.
• We translate business requests into analytical questions, perform analysis and modeling, and communicate findings to non-technical colleagues with clear business recommendations.
• We manage project milestones, risks, and impediments, and escalate potential issues that could affect delivery.
• We establish and maintain best practices for working with Data Engineering and IT to deploy production-ready analytical assets aligned with modeling and risk management standards.
• We engage with internal and external peers and managers to stay current on leading techniques, technologies, and methods.
• We mentor data scientists in modeling, analytics, computer science, business judgment, and interpersonal effectiveness.
• We participate in enterprise-wide efforts that advance and modernize data science technologies and culture.
• We ensure business risks are identified, measured, monitored, and controlled in line with risk and compliance policies and procedures.

• AI
• Support
• JSON
• Machine Learning
• NoSQL
• Python
• SQL
• Security
• XML

More:

We are USAA, and our mission is to help our members achieve financial security through competitive products, exceptional service, and trusted advice. We serve the military community and their families, and our values of honesty, integrity, loyalty, and service guide how we work with one another and with our members. We support active-duty military spouses, and this role may offer remote or hybrid flexibility for active-duty military spouses in line with applicable policy and business needs. This opportunity is remote-eligible within the continental U.S. with occasional business travel, though candidates living within 60 miles of a USAA office are expected to work on-site four days per week. Relocation assistance is not available. The salary range for this position is $164,780 to $314,960, and employees may be eligible for pay incentives based on corporate and individual performance at the discretion of our Board of Directors. We do not provide visa sponsorship for this role.

last updated 36 week of 2026