Data Scientist, Mid-level – Risk Modeling

USAA

. Gather, interpret, and manipulate structured and unstructured data for advanced analytical solutions .

Posted 10/7/2026full-timeUnited StatesMid-LevelSenior💰 $114,080 - $218,030 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in predictive analytics and data analysis, with a strong focus on developing and deploying machine learning models. Proficient in translating complex analytical results into actionable business insights while ensuring compliance with risk management frameworks.

Highest-signal resume keywords

Predictive AnalyticsMachine Learning Model DevelopmentPython or R ProgrammingSQL QueryingRisk Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalysisStatistical ModelingMachine LearningData PreprocessingLinear/Logistic RegressionDecision TreesK-Means ClusteringSupport Vector MachinesAd-Hoc AnalyticsModel Validation

Soft Skills

Attention to DetailCollaborationCommunication

Tools & Technologies

SQLHQLNoSQLJSONXML

Industry Keywords

P&C InsuranceRisk ManagementModel Development ControlModel Risk Management

Tech Stack

Tools & technologies

NoSQLPythonSQL

About the role

Key responsibilities & impact

Gather, interpret, and manipulate structured and unstructured data for advanced analytical solutions
Develop scalable, automated solutions using machine learning, simulation, and optimization
Select modeling techniques and technologies based on data limitations, application, and business needs
Develop and deploy models within the Model Development Control and Model Risk Management frameworks
Compose technical documents for knowledge persistence, risk management, and technical review audiences
Assess business needs and propose or recommend analytical and modeling projects
Prioritize analytics and modeling problems and research efforts with business and analytics leaders
Contribute to reusable, production-quality algorithms and supporting code
Translate business requests into analytical questions, perform analysis or modeling, and communicate outcomes to non-technical colleagues
Collaborate with Data Engineering, IT, business teams, and internal stakeholders to deploy production-ready analytical assets
Maintain awareness of cutting-edge techniques
Learn new techniques, technologies, and methodologies
Identify, measure, monitor, and control business risks according to risk and compliance policies

Requirements

What you’ll need

Bachelor's degree in Mathematics, Computer Science, Statistics, Economics, Finance, Actuarial Science, Science, Engineering, or a quantitative field; OR 4 years of relevant education and/or experience
4 years of experience in predictive analytics or data analysis; OR an advanced degree and 2 years of experience in predictive analytics or data analysis
2 years of experience training and validating statistical, physical, machine learning, and other advanced analytics models
2 years of experience using a dynamic scripted language such as Python or R for statistical analyses and/or building and scoring AI/ML models
Experience writing easy-to-follow, well-documented, transparent code
Experience querying and preprocessing structured and/or unstructured database data using SQL, HQL, NoSQL, or similar query languages
Experience working with structured, semi-structured, and unstructured data files, including numeric delimited files, JSON/XML, text documents, and images
Experience performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics
Ability to assess regulatory implications and expectations of modeling efforts
Experience with classical supervised modeling techniques, including linear/logistic regression, discriminant analysis, support vector machines, decision trees, and forest models
Experience with unsupervised modeling techniques, including k-means, hierarchical/agglomerative clustering, neighbors algorithms, and DBSCAN
Experience communicating analytical and modeling results to non-technical business partners with business recommendations and actionable applications
Risk modeling experience
Experience building and deploying machine learning models in production
P&C Insurance domain experience
Experience solving ambiguous data problems
Experience working collaboratively with multiple stakeholders
Strong attention to detail
Must not require immigration support or visa sponsorship now or in the future

Benefits

Comp & perks

Remote or hybrid flexibility may be offered for active-duty military spouses, consistent with policy and business needs
Pay incentives may be available based on overall corporate and individual performance, at the discretion of the USAA Board of Directors
Comprehensive medical, dental, and vision plans
401(k)
Pension
Life insurance
Parental benefits
Adoption assistance
Paid time off program
Paid holidays
16 paid volunteer hours
Wellness programs
Career path planning
Continuing education assistance