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职位JPMorgan Chase

Data Scientist Associate - APAC Payments Data & Analytics

JPMorgan Chase

Data Scientist Associate - APAC Payments Data & Analytics

JPMorgan Chase

Mumbai, Maharashtra, India, IN

·

On-site

·

Full-time

·

3w ago

必备技能

AWS

Tableau

Our Payments Data and Analytics team is responsible for delivering high impact insights to help grow our payments business, driving our Payments data strategy, and creating innovative data-driven products for our clients and internal partners. We combine data science/AI/ML expertise, consultative problem solving, design thinking and a deep understanding of technology to drive value.

As an APAC Data Scientist, you will collaborate with our global data science and product teams to deliver high-impact AI & Analytics use cases and drive the adoption of our global solutions. You will engage with stakeholders to showcase our data-driven products, gather feedback and identify new opportunities for insights and product enhancements.

Job responsibilities:

  • Explore how money moves through our network and around the world - working in close partnership with teams selling, developing and creating Payments’ products, including consumer-to-business payments, FX, trade finance and more, turning data into insights to impact the strategy and direction of JPM products.
  • Forge close partnerships with internal stakeholders to identify complex data requirements and deliver insights that increase revenue and improve client outcomes.
  • Identify and explore opportunities to integrate Agentic AI workflows in business operations
  • Follow a management consulting type approach to identify and prioritize use cases (through impact orientation, business understanding, program management, executive presence)
  • Combine strong analytical thought process with hands on technical skills to solution and advance thinking to "best in class"
  • Articulate concisely complex information in communicating to internal stakeholders
  • Collaborate with product managers to contribute to the development of robust data assets that power analytical solutions

Required qualifications, capabilities, and skills:

  • 4+ years of relevant experience in Data Science, Analytic Solutions and GenAI/Agentic AI use cases
  • Bachelor's Degree in Engineering /Computer Science/ Statistics/Mathematics or other relevant fields
  • Expertise in data and analytics platforms, leveraging a range of data mining and data visualization tools such as Databricks, PySpark, Tableau etc.
  • Exposure to building AI powered solutions including working knowledge of LLMs, prompt engineering, RAG/MCP based integrations etc.
  • Experience in cloud computing platforms such as AWS

Preferred qualifications, capabilities, and skills:

  • Experience in creating Agentic AI solutions and fluency with the different large language models
  • Experience in the payments industry and/or technology-enabled industries
  • Management consulting experience is a plus
  • Builds trust based relationships with partners across teams and functions

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关于JPMorgan Chase

JPMorgan Chase

JPMorgan 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