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Senior Analyst-Data Science

Gurugram, HR, India

Pay
Pay not listed
Work setting
Hybrid — work setting source
Work setup in the employer’s listing: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting
Apply at American Express

What you’ll work on

Full posting
  • Develop, deploy and validate predictive models for risk, fraud and marketing decisions

  • Analyze large amounts of data to derive business insights and innovative solutions

  • Use closed-loop data from the Amex network to make decisions more relevant

  • Present business findings clearly to leadership and key partners

From the employer’s posting
Development, deployment and validation of predictive model(s)
Analyze large amounts of data to derive business insights and create innovative solutions
Leverage the power of closed loop through Amex network to make decisions more intelligent and relevant
Clear articulation and structuring of business findings across prospect and customer domain to the leadership and key partners

What you’ll bring

All qualifications

Core experience

  • 24-48 months of experience in analytics or big data work
  • MBA or master's in economics, statistics, computer science or related field
  • Proficiency in SAS, R, Python, Hive, Spark and SQL
  • Experience with supervised and unsupervised machine learning techniques

Preferred experience

  • Expertise in coding, algorithms and high performance computing
Qualification wording
24-48 months of experience in analytics, big data workstreams.
MBA, master’s degree in economics, Statistics, Computer Science Or related fields
Worldwide SAS, R, Python, Hive, Spark, SQL
Unsupervised and supervised techniques
Expertise in Coding, Algorithm, High Performance Computing
Education & alternatives
Minimum Qualifications - MBA, master’s degree in economics, Statistics, Computer Science Or related fields - 24-48 months of experience in analytics, big data workstreams.

Tools in this posting

  • Python
  • R
  • SAS
  • Hive
  • Spark
  • SQL
Source — Tool mentions in context
- Ability to Integrate with Cross-Functional Business Partners Worldwide - SAS, R, Python, Hive, Spark, SQL - Unsupervised and supervised techniques -: active learning, transfer learning, neural models, Decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, Map Reduce techniques, attribute engineering

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Status in our records
Live
First seen by us
Oct 16, 2026 · 5 days ago
Recorded sightings
34
Last seen by us
Oct 21, 2026
Reposted
once since Oct 8, 2026

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Job description

View original posting ↗

Overview of the Business: 

Credit and Fraud Risk (CFR) team helps drive profitable business growth by reducing the risk of fraud and maintaining industry lowest credit loss rates. It uses an array of tools and ever-evolving technology to detect and combat fraud, minimize the disruption of good spending, and provide a world-class customer experience. The team leads efforts that leverage data and digital advancements to improve risk management as well as enable commerce and drive innovation. 

A single decision can have many outcomes. And when that decision affects millions of customers, it needs to be the right one. That’s where our Credit & Fraud Risk (CFR) Analytics & Data Science CoE team comes in. The team leads efforts that leverage data and digital advancements to improve risk management as well as enable commerce and drive innovation, every day. Right from targeting the right customer for our products to underwriting them to managing their experience with Amex when they get onboarded, every decision is advised by groundbreaking analytics & data science. We help the company grow its business profitably while delivering the world's best customer experience, all powered by data. We are the backbone of all financial services operations at American Express and impact every aspect of the company.

As a part of the team, you’ll have the opportunity to work in one of the best companies for data scientists in the country. You will solve real world business problems while getting exposure to the industry’s top leaders in analytics, data science and machine learning. If you’re passionate about solving complex problems and crafting solutions that impact millions, you should consider a career in CFR.

Description on the role 

Development, deployment and validation of predictive model(s) and supporting use of models in economic logic to enable profitable decisions across risk, fraud and marketing.

Responsibilities:  

  • Understand the core business of AXP and the levers behind various decisions
  • Analyze large amounts of data to derive business insights and create innovative solutions 
  • Leverage the power of closed loop through Amex network to make decisions more intelligent and relevant 
  • Innovate with a focus on developing newer and better approaches using big data & machine learning solution 
  • Clear articulation and structuring of business findings across prospect and customer domain to the leadership and key partners
  • Maintain external lens and be aware of developments in the field of Finance/Payments/Analytics etc.

Minimum Qualifications 

  • MBA, master’s degree in economics, Statistics, Computer Science Or related fields 
  • 24-48 months of experience in analytics, big data workstreams.
  • Ability to work effectively in a team environment 
  • Ability to drive project deliverables to achieve business results 
  • Strong communication and interpersonal skills 
  • Innovative problem solver with ability to learn quickly and work independently with complex, unstructured initiatives 
  • Ability to Integrate with Cross-Functional Business Partners Worldwide 
  • SAS, R, Python, Hive, Spark, SQL 
  • Unsupervised and supervised techniques -: active learning, transfer learning, neural models, Decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, Map Reduce techniques, attribute engineering

 

Preferred Qualifications  

•            Expertise in Coding, Algorithm, High Performance Computing  

Source details

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Location & working pattern

Gurugram, HR, India

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