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Full-Time

Lead Data Scientist

Fraud Identity Analytics

Confirmed live in the last 24 hours

USAA

USAA

10,001+ employees

Financial services for military members and families

Financial Services

Compensation Overview

$159k - $286.1kAnnually

+ Pay Incentives

Senior

Remote in USA

This position can work remotely in the continental U.S. with occasional business travel.

Category
Data Science
Data & Analytics
Required Skills
Python
NoSQL
Data Science
R
SQL
Data Analysis
Requirements
  • 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.
  • 8 years of experience in a predictive analytics or data analysis
  • 6 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.
  • Expert ability to write 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.
  • Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
  • Proven ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
  • Project management experience that demonstrates the ability to anticipate and appropriately manage project landmarks, risks, and impediments. Demonstrated history of appropriately communicating potential issues that could limit project success or implementation.
  • Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic models, discriminant analysis, support vector machines, decision trees, forest models, etc.
  • Expert level experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
  • Demonstrated experience in guiding and mentoring junior technical staff in business interactions and model building.
  • Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science.
  • A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent).
  • Extensive technical skills, consulting experience, and business savvy to collaborate with all levels and subject areas within the organization.
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.
  • Develops and mentors junior staff, establishing a culture of R&D to augment the day-to-day aspects of the job.
  • Gathers, interprets, and manipulates sophisticated structured and unstructured data to enable sophisticated analytical solutions for the business.
  • Leads and conducts sophisticated analytics demonstrating machine learning, simulation, and optimization to deliver business insights and achieve business objectives.
  • Guides team on selecting 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 peer reviews technical documents for knowledge persistence, risk management, and technical review audiences.
  • Partners with business leaders from across the organization to proactively identify business needs and proposes/recommends analytical and modeling projects to generate business value.
  • Works with business and analytics leaders to prioritize analytics and highly sophisticated modeling problems/research efforts.
  • Leads efforts to build and maintain 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.
  • Assists team with translating business request(s) into specific analytical questions, implementing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations.
  • Manages project portfolio breakthroughs, risks, and impediments. Anticipates potential issues that could limit project success or implementation and intensifies as needed.
  • Establishes and maintains 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.
  • Interacts with internal and external peers and management to maintain expertise and awareness of pioneering techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
  • Serves as a mentor to data scientists in modeling, analytics, computer science, eye for business, and other interpersonal skills.
  • Participates in enterprise-level efforts to drive the maintenance and transformation of data science technologies and culture.
  • Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

USAA provides financial services specifically for the military community, including active-duty members, veterans, and their families. They offer a variety of products such as auto, home, life, and health insurance, as well as banking services like checking and savings accounts, credit cards, loans, and mortgages. Their retirement services include investment options and personalized financial planning. USAA operates on a membership model, allowing only military members and their families to join, which helps them understand and meet the unique financial needs of this community. This exclusivity sets them apart from competitors. The company aims to promote financial wellness among its members by providing resources and advice for managing debt, planning for deployment, buying homes, and preparing for retirement. USAA is also committed to corporate responsibility, focusing on building resilient communities and addressing issues like housing and food security.

Company Stage

N/A

Total Funding

N/A

Headquarters

San Antonio, Texas

Founded

N/A

Simplify Jobs

Simplify's Take

What believers are saying

  • USAA's investment in digital tools and platforms enhances customer experience, reflecting its adaptability and commitment to innovation.
  • The company's focus on military appreciation and partnerships, such as with the Frisco RoughRiders, strengthens its brand loyalty within the military community.
  • Despite layoffs, USAA's continued hiring and filling of over 8,300 jobs this year indicate robust growth and adaptation to changing business needs.

What critics are saying

  • The recent layoffs and top-level departures, including the upcoming retirement of CEO Wayne Peacock, could lead to instability and affect employee morale.
  • USAA's poor ratings from the Office of the Comptroller of the Currency in 2023 and 2022 highlight potential regulatory challenges and reputational risks.

What makes USAA unique

  • USAA's exclusive membership model allows it to deeply understand and cater to the specific financial needs of the military community, unlike broader financial institutions.
  • The company's leadership, with many having military backgrounds, ensures a strong alignment with the values and needs of its members, setting it apart from competitors.
  • USAA's commitment to corporate responsibility and community resilience initiatives further distinguishes it as a socially responsible financial services provider.

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