Analyst – Data Science
American Express — Hybrid - Gurugram
₹4–8 LPA (HireSetu estimate) · Entry level · Freshers eligible · Full-time · hybrid
HireSetu listing reference 378b7f — confirm requirements below, then apply on the employer site.
Quick answer: A credit and fraud risk modelling role at Amex, open to anyone from fresher to 30 months of experience, as long as you hold a master's or MBA. The modelling methods list is far longer than any one person's background.
From American Express's job posting
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.
Qualifications
- MBA, master’s degree in economics, Statistics, Computer Science Or related fields
- 0-30 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
As part of Team Amex, you’ll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.
The employer’s company overview, benefits and equal-opportunity statement are left out here; they are on the original posting.
Text from American Express's official job posting, formatted by HireSetu. The employer's own page is the final word on details.
HireSetu's note
The degree is the gate
The experience band is wide, 0 to 30 months, so a fresh master's graduate and someone with two years at a bank or fintech both fit. The qualification line is not wide: an MBA or a master's in economics, statistics or computer science. A bachelor's degree alone gets screened out before your projects are read, so if you're mid-master's, apply when you can give a clear completion date.
Economics and statistics graduates sit alongside CS ones here, which tells you the analytical training counts for more than the department name on your certificate.
A methods list nobody covers
Supervised and unsupervised learning sits in the same sentence as neural models, Gaussian processes, reinforcement learning, graphical models, Bayesian methods, active learning, transfer learning and MapReduce. Read that as a menu of research areas, not a checklist for one hire.
Pick the two or three you can explain line by line, with a project behind each, and let those carry your CV. A resume listing every term on that page reads as surface-level, and anyone reading it can tell within a minute.
Building, deploying and validating are separate jobs
The role spans all three phases of a model's life, and validation is the part freshers underestimate. It means independently checking someone else's model: the data it was trained on, its assumptions, whether the numbers hold up, and writing up what you find. Habits from software testing transfer well.
The outputs feed decisions on fraud blocks, credit lines and marketing offers, so people outside the team read them. Hive and Spark in the tool list mean the data is too big for a laptop; get comfortable writing a join or aggregation over a large table and think about how you would sample it while testing.
Order your CV around evidence
Python and SQL first, then Hive or Spark if you have either. One project described end to end, from raw data through cleaning and modelling to a result you can defend, says more than five listed in a single line.
If you have touched transaction, credit or fraud data, even in an internship, put that at the top of the page. It is the closest thing to the raw material this team works with.
Drafted with AI from American Express's job posting and checked by Prashanth Jakkula before publishing. See our Editorial Policy.
How to apply
- Open American Express's careers site with the Apply button.
- Enter your email address; Oracle sends a one-time code instead of asking for a password.
- Upload your resume or fill in the profile form, then answer the questions for this role.
- Submit and keep the confirmation email, which also lets you track the application.
Apply on American Express's site
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