招聘

AI/ML Capabilities – Associate, APAC Chief & Data Analytics Office
Singapore, Singapore, SG
·
On-site
·
Full-time
·
3w ago
The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is pivotal in advancing the firm's data and analytics capabilities, ensuring strong adherence to data & AI risk & control while enabling the data & analytics strategy for superior decision-making and business outcomes to serve our clients and markets. By leveraging data & AI/ML, the CDAO develops innovative solutions to support commercial goals, enhance productivity, and manage risks. The Asia Pacific Chief Data & Analytics Office (CDAO) advances the firm’s data and analytics strategy, platforms, solutions, capabilities, and governance to deliver trustworthy, responsible, innovative, and commercially valuable outcomes across the APAC markets and businesses.
As an Associate in AI/ML Capabilities, APAC, the individual supports the team in building, enhancing, and scaling AI/ML platforms and tools across the region. The Associate assists in the development, testing, and deployment of AI/ML solutions, helps document technical requirements, and contributes to knowledge sharing and continuous improvement.
Key Responsibilities
- Assist in identifying opportunities for new or improved AI/ML capabilities by gathering and analyzing business and technical requirements.
- Support the design, development, and deployment of AI/ML platforms, tools, and frameworks.
- Help ensure AI/ML solutions are robust, reusable, and compliant with governance standards.
- Contribute to project plans, timelines, and success metrics for AI/ML capability initiatives.
- Promote best practices in AI/ML development, testing, and deployment within the team.
- Support knowledge sharing and continuous learning across functions.
- Conduct research on emerging technologies, industry trends, and regulatory changes in the AI/ML space.
- Prepare presentations, reports, and documentation for stakeholders.
- Assist in ensuring compliance with data management, governance, and regulatory requirements.
Required Qualifications, Capabilities, and Skills
- Bachelor’s degree in Computer Science, Artificial Intelligence, Engineering, Mathematics, or a related quantitative field.
- 3+ years of experience in AI/ML, data science, analytics, or technology roles, ideally within financial services.
- Foundational understanding of AI/ML concepts, frameworks, and tools.
- Experience supporting the development and deployment of AI/ML platforms and solutions.
- Basic technical knowledge to work effectively with engineering teams.
- Experience working in cross-functional teams.
- Strong analytical, problem-solving, and communication skills.
- Ability to help translate business needs into technical requirements.
- Awareness of APAC regulatory requirements and cultural diversity.
Preferred Qualifications, Capabilities, and Skills
- Exposure to building or customizing AI/ML platforms and workflows.
- Interest in ethical AI/ML practices and governance frameworks.
- Experience or interest in the financial services industry, especially in APAC.
- Experience working with or supporting globally distributed teams.
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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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