运营与AI风险负责人
Lead Operational and AI Risk Manager
我们正在寻找有才华的专业人士,与我们一同将智能财务管理及支付解决方案带到每个人的指尖。
<<>><<>><<>><<>><<>><<>><<>><<>><<>><<>>
职位描述
此职位可在全美任何地方远程工作。
职位简介
首席运营风险经理是一位多面手的风险专业人员,支持非金融风险组织内的多种分析、监督和监管重点。该职位通过数据、良好的判断力和跨职能合作,帮助识别重要风险,评估业务实践和防护措施是否按预期运行,并将复杂信息转化为清晰的风险管理建议,供风险领导层和高管利益相关者参考。
该职位通过专业知识、影响力、项目领导力和跨职能协作提供领导力。
该职位适合一位充满好奇心、适应性强并能自如应对不同业务问题的人。成功候选人将独立领导复杂的分析和风险监督计划,在模糊情况下做出重大判断,并为复杂的业务和监管挑战制定实际且可持续的解决方案。该职位还涉及与AI相关的模型监督,并支持在风险职能中负责任地采用AI。
主要职责
数据分析与管理报告
• 从多个来源查找、整理和分析数据,以识别趋势、异常和需要管理层关注的领域。
• 为风险负责人和高级管理层开发清晰的报告、仪表板、指标和演示文稿。
• 在评估风险和业务防护措施的有效性时,帮助加强客观证据和可衡量结果的使用。
• 与业务和技术合作伙伴合作,了解数据需求,确认数据质量,并改善对有用信息的访问。
风险审查与业务合作
• 评估重要的业务流程、运营活动和变更,以识别潜在风险和实际的改进机会。
- 领导涉及风险、技术、合规、审计和业务利益相关者的跨职能计划,以支持监管承诺、整改活动和战略目标。
- 为业务和风险利益相关者在复杂的风险管理、分析、模型监督和控制相关事项方面提供咨询和指导。
• 评估政策、程序和监控措施是否有效。
查看英文原文
We’re looking for talented professionals to join us in bringing smart money management and payment solutions to everyone’s fingertips.
<<>><<>><<>><<>><<>><<>><<>><<>><<>><<>>
JOB DESCRIPTION
This role can work remotely anywhere in the United States.
Job Summary
The Lead Operational Risk Manager is a versatile risk professional who supports a range of analytical, oversight, and regulatory priorities within the Non-Financial Risk organization. The role uses data, sound judgment, and cross-functional partnership to help identify important risks, evaluate whether business practices and safeguards are working as intended, and turn complex information into clear recommendations for risk leadership and executive stakeholders.
The position provides leadership through expertise, influence, project leadership, and cross-functional collaboration.
This position is well suited for someone who is curious, adaptable, and comfortable moving between different business problems. The successful candidate will independently lead complex analytical and risk oversight initiatives, exercise significant judgment in ambiguous situations, and develop practical, sustainable solutions to complex business and regulatory challenges. The role also includes AI-related model oversight and supports responsible AI adoption across the risk function.
Key Responsibilities
Data Analysis and Management Reporting
• Find, organize, and analyze data from multiple sources to identify trends, anomalies, and areas requiring management attention.
• Develop clear reports, dashboards, metrics, and presentations for risk leaders and senior management.
• Help strengthen the use of objective evidence and measurable outcomes when assessing risk and the effectiveness of business safeguards.
• Work with business and technology partners to understand data needs, confirm data quality, and improve access to useful information.
Risk Reviews and Business Partnership
• Assess significant business processes, operational activities, and changes to identify potential risks and practical opportunities for improvement.
- Lead cross-functional initiatives involving Risk, Technology, Compliance, Audit, and business stakeholders to support regulatory commitments, remediation activities, and strategic objectives.
- Provide consultation and guidance to business and risk stakeholders regarding complex risk management, analytics, model oversight, and control-related matters.
• Evaluate whether policies, procedures, monitoring, and other safeguards are appropriately designed and operating as intended.
• Partner with business teams to understand issues, challenge assumptions constructively, and develop practical recommendations.
• Support the resolution of identified issues and help management track important commitments through completion.
Model and Analytical Tool Reviews
• Support independent reviews of models and analytical tools used to make or inform business decisions.
• Analyze model design, inputs, outputs, performance, limitations, and ongoing monitoring using a risk-based approach.
• Prepare clear documentation that explains the work performed, conclusions reached, and any recommended improvements.
• Collaborate with model owners, data teams, and technical specialists to resolve questions and improve ongoing oversight.
AI Model Validation and Responsible AI Adoption
• Lead the independent validation of a regulatory model with AI and LLM components, including assessment of model design, inputs, outputs, performance, and known limitation, while serving as a key subject matter expert on model governance, validation methodologies, and responsible AI practices.
• Apply structured LLM evaluation methods — including benchmark testing, output consistency checks, adversarial prompting, and bias assessment — to evaluate model reliability and fitness for regulatory use.
• Prepare validation documentation that clearly explains methodology, findings, limitations, and recommended actions in a format suitable for regulatory review.
• Actively use AI tools in day-to-day risk work — including analysis, drafting, and research — and identify opportunities to improve the efficiency and quality of risk oversight through AI-enabled workflows.
• Assess emerging AI tools and associated risks, contributing to governance considerations and practical implementation guidance as the function’s AI capabilities mature.
Fraud Risk and Program Effectiveness
• Assess fraud prevention, detection, monitoring, and response practices using available data and performance information.
• Analyze fraud trends and outcomes to identify gaps, emerging concerns, and opportunities to strengthen the program.
• Help translate fraud data and operational observations into clear conclusions and recommendations for management.
Regulatory and Strategic Priorities
• Support regulatory examinations, internal reviews, remediation efforts, and other time-sensitive risk initiatives.
• Conduct focused research and analysis on emerging or complex business issues.
• Provide flexible support across the Risk organization as priorities evolve, while maintaining accountability for high-quality and timely work and independently driving complex initiatives from problem definition through recommendation and implementation support.
• Build productive working relationships across business, technology, compliance, audit, and risk teams.
Required Qualifications
• Bachelor's degree in business, finance, economics, mathematics, statistics, data analytics, information systems, risk management, or a related field.
• At least 7 years of relevant experience in risk management, fraud, model oversight, data analytics, or a related discipline.
• Experience in banking, fintech, payments, or another regulated financial services environment.
• Demonstrated ability to locate, interpret, and analyze data and translate findings into practical business insights.
• Strong problem-solving skills and the ability to work independently through ambiguous or complex assignments.
• Clear written and verbal communication skills, including the ability to explain technical or complex matters to non-technical audiences.
• Ability to build effective relationships and work across organizational boundaries in a remote environment.
• Comfortable using AI tools as part of everyday work, including large language models and AI-assisted research or analysis tools.
Preferred Qualifications
• Experience evaluating business processes, controls, or risk management programs.
• Experience supporting regulatory examinations, internal audits, or remediation programs.
• Experience with fraud analysis, model reviews, statistical analysis, or performance monitoring.
• Experience using data analysis, visualization, reporting, or governance tools.
• Working knowledge of SQL, Python, Power BI, Tableau, or similar tools is beneficial.
• Familiarity with LLM evaluation techniques, including benchmark testing, output consistency assessment, or bias analysis, particularly in a model validation or oversight context.
• Experience using AI tools in day-to-day work, with a demonstrated interest in leveraging AI to improve analytical output and amplify the impact of the Risk organization.
Core Capabilities
· Analytical and data-minded
· Intellectual curiosity and willingness to learn
· Adaptable and comfortable with change
· Ownership and follow-through
· Sound judgment and practical problem solving
· Collaborative stakeholder management
- Clear and concise communication
- AI-forward
- Ability to manage competing priorities
- Cross-functional influence without direct authority
**Ability to work in the U.S. without sponsorship**
**Ability to meet the location requirement outlined above**
POSITION TYPE
RegularPAY RANGE
The targeted full-time base salary for this position is $97,100 to $145,500 per year. The final compensation will be determined by a number of factors such as qualifications, expertise, and the candidate’s geographical location.
<<>><<>><<>><<>><<>><<>><<>><<>><<>><<>>
We’re Here to Support You—Accommodations Upon Request
Green Dot is committed to providing an inclusive and accessible hiring experience for all candidates. If you require a reasonable accommodation during any part of the application or interview process, we encourage you to let us know. We will work with you to meet your needs in a way that respects your privacy and ensures equal opportunity. Our goal is to support every applicant in showcasing their talents and potential.
Work Authorization Requirement
At Green Dot Corporation, we value diversity and strive for fair and inclusive hiring practices. However, we are currently unable to offer visa sponsorship. All applicants must be legally authorized to work in the United States at the time of application and throughout the duration of employment, without the need for current or future sponsorship.
Important Notice on Application Accuracy
We value integrity in our hiring process. Please ensure that all information provided in your resume and application is accurate and authentic. Submissions found to be fraudulent or misleading will result in disqualification from consideration, and any offers extended may be rescinded.
Originally posted on Himalayas