USAA

Solutions Engineer

• Gather, interpret, and manipulate structured and unstructured data to enable 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 recommend analytical and modeling projects
• Prioritize analytics and modeling problems with business and analytics leaders
• Build and maintain reusable, production-quality algorithms and supporting code
• Translate business requests into analytical questions, execute analyses or modeling, and communicate actionable recommendations to non-technical colleagues
• Manage project milestones, risks, and impediments; escalate issues that could limit success
• Develop deployment best practices with Data Engineering and IT
• Maintain awareness of cutting-edge techniques, technologies, and methodologies
• Mentor junior data scientists
• Participate in internal communities supporting data science technology and culture
• Identify, measure, monitor, and control risks in accordance with policies and procedures

Senior AI Data Scientist – Solutions Developer

Full-stack Engineer

• Design, develop, code, and test complex technical solutions
• Investigate and resolve complex application and system technical problems and production issues through troubleshooting techniques
• Conduct complex systems analysis and recommend changes in policies and procedures to improve operations
• Prepare and install complex solutions by determining and designing system specifications, standards, and programming
• Follow the software development lifecycle
• Participate in design reviews and learn key system design principles
• Mentor junior engineers and may begin mentoring peer engineers
• Review teammates' code
• Identify, measure, monitor, and control risks associated with business activities in accordance with risk and compliance policies and procedures
• Collaborate with product and business stakeholders in a sprint-based Agile environment
• Build and modernize services supporting member/customer data platforms

Software Developer – APIs, Data Services

Machine Learning Engineer

• Consult with data scientists and business partners on ML model development and implementation approaches
• Provide technical feedback on ML solutions within the technical lead community
• Lead the full machine learning engineering lifecycle, including analysis, solution design, data pipeline engineering, testing, deployment, scheduling, application integration, production support, and API development
• Support GenAI applications, ML frameworks/libraries, and ML models
• Configure, manage, and set up AI/ML infrastructure in cloud and on-premises environments
• Work with AWS, GCP, and graph databases
• Work with architects to influence and define ML model implementation patterns in complex environments
• Design and implement complex machine learning, artificial intelligence, and GenAI technical solutions
• Create proofs of concept and prototypes for highly complex solutions and present them to leadership
• Assist in setting technical direction for the team
• Mentor team members
• Identify, measure, monitor, and control risks associated with business activities in accordance with risk and compliance policies

Senior AI & Machine Learning Engineer

• Partner with Data Scientists and business stakeholders to align predictive analytics solutions with business objectives
• Develop, test, implement, and integrate processes with business applications using machine learning predictions and classifications
• Refactor machine learning code into IT-maintainable solutions following best practices and coding standards
• Configure, manage, and set up AI/ML infrastructure in cloud and on-premises environments
• Conduct the full machine learning engineering lifecycle, including analysis, solution design, data pipeline engineering, testing, deployment, scheduling, production support, API development, and application integration
• Design and implement complex machine learning, artificial intelligence, and GenAI solutions
• Create proofs of concept and prototypes for complex initiatives
• Collaborate with engineers and teams on new technologies and alternatives
• Develop, maintain, and enforce data development tools and standards
• Conduct regular code reviews to improve quality and ensure compliance
• Identify, measure, monitor, and control risks in accordance with risk and compliance policies

Experienced AI & Machine Learning Engineer

Product Manager

• Translate business needs into actionable product requirements
• Create and manage product features using Jira and Clarity
• Partner with Agile teams to decompose features into user stories and define acceptance criteria
• Maintain a prioritized product backlog
• Facilitate backlog refinement, sprint planning, and ongoing prioritization
• Collaborate with technology teams and guide product delivery from concept through implementation
• Understand business strategy and vision, then write, refine, accept, and prioritize stories and features
• Review and accept IT and/or business development outputs against acceptance criteria
• Represent the business and customers throughout the product delivery cycle
• Collaborate with UX partners, designers, business analysts, developers, testers, and others to develop, execute, and release products
• Define and document business processes with sponsors, stakeholders, and IT
• Prepare the business for change and provide tactics and metrics for benefits, adoption, and risk
• Oversee development, testing, and controls across internal and external technologies
• Enhance and advance the business development/execution function
• Coach and mentor other Product Owners
• Lead development across multiple teams at project or program level
• Identify, measure, monitor, and control risks in accordance with risk and compliance policies and procedures

Senior Data Product Owner – Member Value

Technical Product Manager

• Provide strategic product leadership for enterprise initiatives that drive business value, operational efficiency, and exceptional member experiences
• Partner with senior business leaders, technology teams, and cross-functional stakeholders to define product vision and translate business objectives into technical solutions
• Develop multi-year product roadmaps aligned with organizational priorities
• Lead discovery sessions, evaluate business value, and facilitate funding, prioritization, and delivery strategy discussions
• Identify opportunities using research, business and market intelligence, and data-driven insights
• Translate product and experience opportunities into initiatives, requirements, epics, and features, and drive execution strategy
• Shepherd complex and strategic product opportunities from idea through market validation
• Drive, quantify, and defend product and experience investments through business cases and hypotheses
• Analyze and report product performance against KPIs and KRIs
• Generate insights to identify opportunities for product improvements and ensure improvements are implemented
• Prepare presentations and communications for diverse audiences, including senior leadership
• Facilitate product definition, concept, discovery, development, delivery, and validation sessions
• Conduct internal and external research and situational analysis to apply industry best practices and trends
• Manage ambiguity, influence stakeholders, drive clarity, and establish execution plans
• Provide guidance and mentoring to team members and act as an escalation point
• Identify, measure, monitor, and control risks in accordance with risk and compliance policies

Lead Technical Product Owner – Member Value

• Translate business needs into actionable product requirements for successful solution delivery
• Create and manage product features using Jira and Clarity
• Partner with Agile teams to decompose features into user stories and define acceptance criteria
• Maintain prioritized product backlogs for one or more Agile teams
• Facilitate backlog refinement, sprint planning, and ongoing prioritization
• Collaborate with technology teams and guide product delivery from concept through implementation
• Understand business strategy and vision and write, refine, accept, and prioritize stories and features
• Review and accept IT and business development outputs against acceptance criteria
• Represent the business and customer perspective throughout the product delivery cycle
• Participate in cross-functional teams to develop, execute, and release products aligned with roadmaps
• Define and document business processes with sponsors, stakeholders, and IT
• Prepare the business for change and provide tactics and metrics for benefits, adoption, and risk
• Oversee development, testing, and controls across internal and external technologies
• Seek opportunities to enhance and advance the business development/execution function
• Coach and mentor other Product Owners
• Lead development across multiple teams at project or program level
• Identify, measure, monitor, and control risks in accordance with risk and compliance policies

Senior Data Product Owner – Insurance Pricing and Claims

Compliance

• Lead strategic direction across data domains covering information governance, data management, data quality, information architecture, and information asset management
• Work within the Agile community and with leadership to prioritize and fund capability delivery across the Association and data domains
• Direct and collaborate with business and IT partners to use information governance and management capabilities to achieve operational and strategic objectives
• Advise leadership on institutionalizing and maturing information governance, data management, data quality, information architecture, and information asset management capabilities
• Advise on mitigating risk and addressing regulatory requirements related to information governance and management
• Partner with business, risk, compliance, architecture, and IT teams to improve the effectiveness and value of data governance and management processes
• Ensure team activities align with information governance, data management, data quality, information architecture, technical solutions, and information asset management activities
• Direct team work assignments, problem resolution, risk mitigation, and quality work production
• Provide leadership, motivation, oversight, and an environment for building high-performing teams
• Collaborate with Association stakeholders to define capabilities that deliver business value and solve business challenges
• Ensure business activity risks are identified, measured, monitored, and controlled according to risk and compliance policies and procedures

Director, Data Governance – Compliance

• Lead development, implementation, and ongoing management of enterprise data policies and standards supporting regulatory compliance and sound data governance
• Translate complex regulatory requirements into actionable data policies, standards, controls, and governance practices
• Drive adherence to information and data management governance activities, projects, and approaches
• Increase business awareness of information and data governance through consulting and communications with business, technology, security, legal, risk, and compliance partners
• Author or contribute to information governance guidelines, principles, policies, and standards
• Lead information governance oversight processes, measurement approaches, audits, peer reviews, and KRI/KPI monitoring
• Influence and support multi-year roadmaps and implementation plans for information governance initiatives
• Apply business, channel, application, and process knowledge to recommendations addressing regulatory and internal information governance requirements
• Create information governance training content and establish learning objectives
• Prepare and present formal findings and recommendations to all organizational levels
• Incorporate information governance best practices into solution recommendations
• Facilitate career paths, best practices, mentoring, and maturity growth for the Information Governance community
• Ensure business risks are identified, measured, monitored, and controlled according to risk and compliance policies and procedures

Data Policy and Regulatory Governance Lead

Artificial Intelligence

• Lead the development and implementation of AI governance practices for responsible, compliant, and effective AI use
• Establish and mature AI governance frameworks, risk management practices, monitoring processes, and controls
• Monitor and interpret emerging AI regulations, legislation, regulatory guidance, industry standards, and state-level AI laws
• Assist the IMA Director in integrating information management practices into business and technology processes
• Identify and influence process improvements across IMA responsibilities and data spokes
• Lead cross-functional discussions on complex problems
• Align best practices and tools with business needs to improve program efficiency and effectiveness
• Influence prioritization of work based on criticality and risk
• Maintain and validate Information Asset Inventories
• Support delivery of information according to Information Governance standards and data management practices
• Integrate Information Management practices into existing processes and emerging information technologies
• Lead data lineage collection and stitching for complete end-to-end data flow of critical data
• Lead identification and resolution of complex data quality issues
• Design data quality rules, thresholds, and standard quality metrics with the Steward
• Develop process enhancements and data quality plans; oversee implementation of data quality controls
• Define and oversee high-risk data quality corrective action plans
• Oversee compliance assessments and document failures from data quality checks
• Lead data initiatives that mitigate data risk and perform root cause analysis
• Develop Master and Reference Data processes aligned with enterprise policies and standards
• Ensure quality and maintenance of master and reference data
• Identify and escalate items that may pose corporate risk
• Partner with IT and Information Management resources to implement complex Access Management strategies
• Lead Privacy initiatives through classification and analysis of sensitive data
• Ensure compliance and remediation of sensitive data
• Ensure risks associated with business activities are identified, measured, monitored, and controlled

AI Model Governance – Monitoring Lead

• Drive adherence to information/data management governance activities, projects, and approaches compliant with established policies and standards
• Influence business awareness of information/data governance through consulting and communications with business, technology, security, legal, risk, and compliance partners
• Author or contribute to information governance guidelines, principles, policies, and standards
• Lead development of governance oversight processes and measurement approaches
• Enforce adherence through audits, peer reviews, and monitoring of KRIs and KPIs
• Support multi-year roadmaps and implementation plans for information governance initiatives
• Apply business-line, channel, application, and process knowledge to develop recommendations satisfying regulatory and internal requirements
• Create information governance training content
• Prepare and present formal findings and recommendations across the organization
• Promote information governance best practices in solution recommendations
• Facilitate career paths, best practices, mentoring, and maturity growth for the Information Governance community
• Identify, measure, monitor, and control business risks in accordance with risk and compliance policies and procedures
• Monitor and interpret emerging AI regulations, legislation, regulatory guidance, industry standards, and state-level AI laws

Data & AI Governance Lead

QA Engineer

• Drive overall program efficiency and effectiveness and implement techniques and tools supporting data management efforts
• Support information management functions including metadata management, data quality, retention management, and data security
• Document data sources and facilitate Authoritative Data Source certification
• Manage metadata and data lineage within the Enterprise Data Repository
• Ensure data quality, monitor SLAs and data quality metrics, and oversee timely remediation
• Monitor significant changes and ensure timely re-certification
• Assist the IMA Director in integrating information management practices into business and technology processes
• Identify and influence process improvement opportunities across IMA responsibilities and data spokes
• Lead discussions with cross-functional teams on complex problems
• Align best practices and tools with business needs to improve program efficiency and effectiveness
• Influence prioritization of work based on criticality and risk
• Maintain and validate Information Asset Inventories
• Champion delivery of information according to Information Governance standards and data management practices
• Lead integration of Information Management practices into existing and emerging technology processes
• Lead data lineage collection and stitching for complete end-to-end data flow of critical data
• Lead identification and resolution of complex data quality concerns
• Design data quality rules, thresholds, and standard quality metrics for critical data elements
• Develop data quality process enhancements and plans, and oversee implementation of data quality controls
• Define and oversee high-risk data quality corrective action plans
• Oversee compliance assessments and document failures
• Lead Data initiatives, conduct root cause analysis, and identify improvement areas
• Develop Master and Reference Data processes aligned with Enterprise Policies and Standards
• Ensure quality and maintenance of master and reference data
• Identify and escalate items that may pose corporate risk
• Partner with IT and Information Management resources to define and implement complex Access Management strategies
• Lead Privacy initiatives through sensitive-data classification and analysis
• Ensure compliance and remediation of sensitive data
• Ensure risks associated with business activities are identified, measured, monitored, and controlled

Data Quality & Assurance Lead

Data Analyst

• Leverages advanced business, analytical and technical knowledge to participate or lead discussions with cross functional teams to understand and collaborate highly complex business objectives and influence solution strategies.
• Applies advanced analytical techniques to solve business problems that are typically medium to large scale with significant impact to current and/or future business strategy.
• Applies innovative and scientific/quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer the business objective and drive the appropriate change
• Translates recommendation into communication materials to effectively present to various levels of management.
• Incorporates visualization techniques to support the relevant points of the analysis and ease the understanding for less technical audiences.
• Identifies and gathers the relevant and quality data sources required to fully answer and address the problem for the recommended strategy through testing or exploratory data analysis (EDA).
• Integrates/transforms disparate data sources and determines the appropriate data hygiene techniques to apply.
• Thoroughly documents assumptions, methodology, validation and testing to facilitate peer reviews and compliance requirements.
• Understands and adopts emerging technology that can affect the application of scientific methodologies and/or quantitative analytical approaches to problem resolutions.
• Succinctly delivers analysis/findings in a manner that conveys understanding, influences various levels of management, garners support for recommendations, drives business decisions, and influences business strategy.
• Provides subject matter expertise in operationalizing recommendations.
• Remains informed on current data and analytics trends, (Ex: Cloud, Data Mining, Python, Neural Networks, Sensor data, IoT, Streaming/NRT data)
• Identifies opportunities to continue to learn in the data and analytics space, whether informal (E.g., Coursera, Udemy, Kaggle, Code Up, etc.) or formal (E.g. Certifications or advanced coursework).
• Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

Senior Decision Science Analyst – P&C Analytics

• Define, champion, and drive the overall enterprise identity proofing and assurance strategy and roadmap, covering new member enrollment, identity re-verification, step-up proofing, and profile recovery, prioritizing capabilities that produce high-quality, authoritative identity signals while managing member friction appropriately
• Translate business objectives, risk requirements, and member needs into detailed, actionable identity service requirements for technology, architecture, and design teams, encompassing the full identity lifecycle from initial proofing through ongoing assurance maintenance and identity signal reuse across enterprise consumers
• Serve as the organization's subject matter expert on identity verification and identity fraud risk, with deep fluency in third-party identity theft patterns, synthetic identity fraud construction and detection, and the tactical methods by which fraudsters exploit enrollment and re-verification flows
• Drives, quantifies, and defends Digital and Technology product and experience investments through Business Case artifacts and hypotheses, communicating the value proposition of Digital or Technology products and experiences
• Continuously leverages expert data-driven problem-solving techniques and analytical rigor to understand and report on product and experience performance against KPIs/KRIs; shares best practices with team members
• Guides team to generate meaningful insights through a variety of tools and resources to uncover areas of opportunity to inform Digital or Technology product and experience improvements; follows through to ensure applicable improvements are implemented
• Sets the standard for preparing compelling presentations, and other forms of communication to communicate complex concepts to a diverse audience, including senior leadership, and facilitates Digital or Technology product definition, concept and collaboration sessions to coordinate discovery, development, delivery, and validation activities, as well as to mitigate risks and dependencies
• Conducts internal and external research and conducts situational analysis to identify and apply industry best practices and trends to increase effectiveness of Digital or Technology products
• Actively manages ambiguity, influences others to bring in 'big picture' thinking and drives clarity, solutions, and execution plan among team and stakeholders
• Maintains and applies expert knowledge of the business, technology, UX, and relevant experiences and processes and an expert understanding of Product Management
• Consistently provides guidance and mentoring to team members and acts as an escalation point and ensures issues are resolved
• Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures

MIAM Identity Product Lead

• Leverages intermediate business, analytical and technical knowledge to participate in discussions with cross functional teams to understand and collaborate on business objectives and influence solution strategies.
• Applies advanced analytical techniques to solve business problems that are typically medium to large scale with impact to current and/or future business strategy.
• Applies scientific/quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer the business objective and drive the appropriate change.
• Translates recommendation into communication materials to effectively present to colleagues for peer review and senior/lead analysts.
• Incorporates visualization techniques to support the relevant points of the analysis and ease the understanding for less technical audiences.
• Supports identifying and gathering the relevant and quality data sources required to fully answer and address the problem for the recommended strategy through testing or exploratory data analysis (EDA).
• Thoroughly documents assumptions, methodology, validation and testing to facilitate peer reviews and compliance requirements.
• Adopts emerging technology that can affect the application of scientific methodologies and/or quantitative analytical approaches to problem resolutions.
• Delivers analysis/findings in a manner that conveys understanding, influences up to mid level management, garners support for recommendations, drives business decisions, and influences business strategy.
• Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.