招聘

AI & Data Risk Lead (2LoD) - Vice President
LONDON, LONDON, United Kingdom, GB
·
On-site
·
Full-time
·
1mo ago
Join the Data & AI CCOR team that oversees the management and governance of data, privacy and AI risks at the enterprise level and partners closely with CCOR coverage officers across all lines of business, corporate functions, legal entities, and regions. The Data & AI CCOR team supports the Firmwide Chief Data and Analytics Office (FCDAO) to drive consistent risk management practices. And sets minimum requirements for the first line’s identification, management, reporting, and escalation of data, privacy and AI risks, enabling effective second line oversight of operational and compliance risks in accordance with the CCOR framework.
As a Vice President within Data & AI CCOR team you will support the Data and AI CCOR regional and horizontal (line of business/corporate function) program. Responsibilities include supporting line of business and functional CCOR teams to maintain CCOR skill levels, oversee testing programs, own and manage governance, support regulatory engagements and senior level internal reporting. The ideal candidate combines strong program management and stakeholder engagement skills with regulatory knowledge and/or technical data analytics and AI expertise.
Job Responsibilities
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Lead and support the maintenance of the Data and AI CCOR Program across the line of business (LOB), corporate functional (CF) and regional programs covering Data, Privacy, and AI risk.
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Support the oversight of the Chief Data and Analytics Office (CDAO) for LOB/CF and regional teams
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Establish, own and maintain the cross LOB/CF and regional governance model to provide connectivity with the firmwide Data and AI CCOR teams
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Support curated training programs to enhance employee awareness of Data, Privacy and AI obligations.
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Develop data insights through innovative use of AI tools – be a champion of AI innovation in the team.
Maintain expert knowledge of current and future Data, Privacy and AI regulations
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Build and maintain strong relationships with business, control, and operational risk teams across the organization.
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Support the CDAO and CCOR in regulatory exams and internal audits, as required.
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Deliver senior management reporting executed via AI tool streamlining
Required qualifications, capabilities, and skills
- Effective communicator with strong verbal and written skills; ability to synthesize and present to senior audiences
- Proven program and stakeholder management; operates independently and drives results across complex environments.
- Strong analytical and problem-solving skills; relevant experience in Data and/or AI risk management.
- Experience in leading complex programs and delivering results
- Understanding of AI/ML lifecycle & model governance: familiar with end‑to‑end workflows from features to deployment/MLOps with robust documentation and validation.
Preferred qualifications, capabilities, and skills
- Knowledge of data architecture & governance strongly preferred; enterprise data design and controls (lineage, metadata, data quality) with privacy‑by‑design.
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关于JPMorgan Chase

JPMorgan Chase
PublicJPMorgan Chase & Co. is an American multinational banking institution headquartered in New York City and incorporated in Delaware. It is the largest bank in the United States, and the world's largest bank by market capitalization as of 2025.
300,000+
员工数
New York City
总部位置
$500B
企业估值
评价
3.8
10条评价
工作生活平衡
3.2
薪酬
4.1
企业文化
3.8
职业发展
3.0
管理层
2.5
65%
推荐给朋友
优点
Good benefits and compensation
Supportive and collaborative environment
Flexible work arrangements
缺点
Long hours and heavy workload
Management issues and lack of direction
High stress during peak times
薪资范围
41个数据点
Mid/L4
Senior/L5
Mid/L4 · Applied AI ML Associate
2份报告
$188,500
年薪总额
基本工资
$145,000
股票
-
奖金
-
$182,000
$195,000
面试经验
5次面试
难度
3.0
/ 5
时长
14-28周
录用率
40%
体验
正面 20%
中性 80%
负面 0%
面试流程
1
Application Review
2
HireVue Video Interview
3
Recruiter Screen
4
Superday/Panel Interview
5
Final Interview
6
Offer
常见问题
Behavioral/STAR
Technical Knowledge
Culture Fit
Past Experience
Case Study
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