The Senior AI and ML Risk Manager at Huntington primarily focuses on identifying, evaluating, and monitoring risks associated with AI and ML deployments. This includes conducting risk assessments, developing mitigation strategies, liaising with various teams to advise on potential risks, and preparing reports for senior management to highlight areas of concern.

To qualify for the Senior AI and ML Risk Manager position at Huntington, candidates should possess at least a Bachelor’s degree and 7 years of experience in Audit, Compliance, Risk Management, or Operational Risk, alongside 3 years of direct AI and ML experience. Preferred qualifications include advanced knowledge of risk management principles, strong analytical skills, and relevant certifications such as CISSP, CISA, CRISC, or CISM.

Essential skills for success as a Senior AI and ML Risk Manager at Huntington include strong organizational and critical thinking abilities, excellent verbal and written communication skills, and the capacity to navigate complex situations and influence change. Familiarity with AWS cloud environments and Python scripting adds significant value to the role.

At Huntington, the Senior AI and ML Risk Manager position offers a hybrid work environment that blends in-office collaboration with the flexibility of remote work. This setup allows team members to maintain connections while fostering a strong sense of community, essential for effective teamwork.

Huntington supports its Senior AI and ML Risk Managers through continuous training, access to the latest resources, and a collaborative culture that values employee input and innovation. By providing a variety of benefits, including health insurance and retirement plans, Huntington ensures that its employees feel valued and supported.

When responding, think of a specific project where you proactively identified a risk stemming from data quality or compliance issues. Highlight your analytical approach, the steps you took to communicate this risk to stakeholders, and the outcome that resulted from your initiative.

Discuss various strategies you use to remain informed, such as attending conferences, subscribing to industry journals, or participating in relevant online forums. Mention specific sources or networks that are valuable for your understanding of AI and ML advancements.

Share your structured approach to risk assessment, detailing how you identify vulnerabilities through data analysis, stakeholder interviews, and benchmarking against industry standards. Clarify the importance of a comprehensive, team-based approach in this process.

Demonstrate your conflict resolution skills by explaining how you’d listen to their perspective, present your analysis, and seek a collaborative solution. Emphasize the importance of considering all viewpoints before arriving at a consensus.

Highlight specific regulations you've worked with, such as GDPR or CCPA, and how you ensure compliance in AI and ML initiatives. Discuss any frameworks you utilize to evaluate the effectiveness of these compliance measures.

Provide examples of specific risk management tools or software you're proficient in, such as risk registers or audit management platforms, and how they have facilitated your risk assessments and reporting in past roles.

Share a concrete example detailing the risk you identified, the strategy you deployed to mitigate it, and the eventual outcome. Focus on your thought process in devising the strategy and the importance of stakeholder involvement.

Discuss your method for assessing and prioritizing risks based on their potential impact and likelihood of occurrence. Include the criteria you use to make prioritization decisions and how you communicate these priorities to your team.

Identify relevant challenges such as regulatory compliance, data privacy, or ethical considerations. Offer insight into how you would approach mitigating these challenges, drawing on past experiences or strategies.

Explain your approach to building relationships with various teams, including how you would facilitate open communication, set shared goals, and encourage input from all members to create a productive collaborative environment.