Senior Analyst Technology Risk

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them.

Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself.

***Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT.***

The Senior Analyst, Technology Risk will identify, assess, and help manage technology risks associated with machine learning, generative AI, and emerging technologies. This individual contributor role supports the Senior Manager, Technology Risk by executing risk assessments, providing independent review and challenge, and partnering with technology, data science, and business teams to help ensure AI and ML solutions are designed and operated in a safe, ethical, and compliant manner. The role requires strong analytical judgment and the ability to translate complex technical risks into clear, actionable insights while operating within established risk frameworks and governance structures.

What you will do:

• Partner with second line enterprise risk and application teams to define, document, and build ML and AI governance policy, processes, controls, and governance tools.

• Execute technology risk assessments for Machine Learning, Generative AI, and advanced analytics solutions across design, development, deployment, and monitoring phases.

• Perform independent risk review and challenge of AI/ML models, including data sourcing, training approaches, validation methods, and ongoing performance monitoring.

• Support the establishment and ongoing execution of AI/ML risk governance, standards, and control frameworks aligned to the Enterprise Risk Appetite Framework.

• Partner with engineering, data science, product, and business teams to identify risks and embed effective controls into AI/ML systems and processes.

• Assess and support management of third-party and vendor risks associated with AI platforms, tools, models, and data sources.

• Prepare clear risk documentation, assessments, and recommendations for review by the Senior Manager and risk governance forums.

• Monitor emerging regulatory guidance, industry standards, and best practices related to AI, model risk, and responsible AI.

• Contribute to risk metrics, reporting, and materials presented to leadership, risk committees, and second-line partners.

• Exercise independent judgment within established frameworks, provide control feedback and issue identification to the Senior Manager, and escalate significant risks or control gaps in accordance with defined thresholds.

• Contribute analysis and recommendations to risk acceptance decisions (without formal approval authority).

What you will bring:

• Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, Risk Management, or a related field.

• Master’s degree (or relevant experience in lieu of advanced education).

• 4 to 6 years of experience in technology risk, model risk management, cybersecurity, data risk, or related disciplines.

• Hands-on experience performing risk assessments for Machine Learning and/or Generative AI solutions.

• Solid understanding of model and agent development on cloud-based infrastructure.

• Experience working in regulated environments (for example, financial services, insurance, healthcare, or fintech).

• Experience partnering with engineering and data science teams in fast-paced technology environments.

• Strong understanding of AI/ML technologies, including LLMs and model training, validation, and deployment.

• Knowledge of Responsible AI principles, model risk management, and data governance practices.

• Ability to independently assess and challenge complex technical risks using sound judgment.

• Strong written and verbal communication skills, including the ability to explain technical risks to non-technical audiences.

• Highly analytical, detail-oriented, and comfortable working with ambiguity.

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