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USAA

Sells insurance and banking to military families

Data Scientist Senior - Model Development

Data ScienceUpdated on Nov 9
Full-timeRemote in USA

About the Job

Requirements

  • A bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or another similar quantitative discipline, or four additional years of statistics, mathematics, quantitative analytics, or related experience in lieu of a degree.
  • Six years of experience in predictive analytics or data analysis, or an advanced degree in a listed quantitative discipline and four years of predictive analytics or data analysis experience.
  • Four years of experience training and validating statistical, physical, machine learning, or other advanced analytics models.
  • Four years of experience using one or more dynamic scripting languages, such as Python or R, for statistical analyses and/or building and scoring AI/ML models.
  • Experience writing code that is easy to follow, well documented, and appropriately commented to explain logic and maintain high code transparency.
  • Strong experience querying and preprocessing structured and/or unstructured database data using query languages such as SQL, HQL, or NoSQL.
  • Strong experience working with structured, semi-structured, and unstructured data files, including delimited numeric data, JSON/XML files, text documents, and images.
  • Skill 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 concepts and technologies for classical supervised predictive modeling, including linear/logistic regression, discriminant analysis, support vector machines, decision trees, and forest models.
  • Advanced experience with concepts and technologies for unsupervised modeling, including k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, and DBSCAN.
  • Experience guiding and mentoring junior technical staff in business interactions and model building.
  • Experience communicating analytical and modeling results to non-technical business partners, emphasizing recommendations and actionable applications.

Responsibilities

  • Gather, interpret, and manipulate structured and unstructured data to enable advanced analytical solutions for the business.
  • Develop scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and value.
  • Select appropriate modeling techniques and technologies based on data limitations, application, and business needs.
  • Develop and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.
  • Compose and assist peers with composing technical documents for knowledge persistence, risk management, and technical review audiences.
  • Assess business needs and recommend analytical and modeling projects; work with business and analytics leaders to prioritize analytics and modeling problems and research efforts.
  • Build and maintain a robust library of reusable, production-quality algorithms and supporting code to ensure model development and research are transparent and based on high-quality data.
  • Translate complex business requests into analytical questions, execute the analysis and/or modeling, and communicate outcomes to non-technical colleagues with business actions and recommendations.
  • Manage project milestones, risks, and impediments, and escalate potential issues that could limit project success or implementation.
  • Develop best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards.
  • Maintain expertise in current techniques and seek opportunities and materials to learn new techniques, technologies, and methodologies.
  • Mentor junior data scientists in modeling, analytics, and computer science tasks.
  • Participate in internal communities that maintain and transform data science technologies and culture.
  • Ensure business risks are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

Desired Qualifications

  • Experience in a medium or large bank.
  • Strong knowledge of Python and/or SAS.
  • Experience collaborating with control partners.
  • Knowledge of Model Risk Management, Model Governance, and regulatory requirements.

About the Company

USAA

Sells insurance and banking to military families

USAA sells insurance, banking and investment products to U.S. military members, veterans and their families, and membership is limited to that community and eligible relatives. It began when Army officers who struggled to get car coverage agreed to insure each other, and auto and home insurance remain its core business. Members can also open checking and savings accounts, carry credit cards, take out auto loans and mortgages, and buy life insurance, annuities and retirement accounts. The company earns money from insurance premiums, loan interest, card fees and investment management. USAA was founded in 1922 and is based in San Antonio, Texas.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
San Antonio, TX
Founded
1922

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