American Express Hiring Drive 2024 For Analyst – Data Science | Location Gurgaon

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American Express Hiring Drive 2024: American Express Hiring Drive 2024 for its Analyst – Data Science. American Express Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a master’s degree in economics, Statistics, or Related Fields. if you are interested, please apply as soon as possible.

Company Name: American Express

Role: Analyst – Data Science

Location: Gurgaon

Experience: 0 – 2 years

Qualification: Master’s degree in economics, Statistics, or Related Fields

Batch: Any

Job Type: Full Time

Salary: 6.0 To 25.5 LPA (Expected)

American Express Hiring Drive 2024

Job Description:

  • Model Risk Management Group (MRMG) within Global Risk and Compliance Group, is responsible for the independent risk management of all American Express (AXP) models.
  • The successful candidate will be responsible to manage and controls model risk, specifically associated to the regulatory models like CCAR, CECL, IFRS9, Economic Capital and Membership Reward.
  • This role will elevate model excellence, strengthen long term shareholder value, and adapt to the changing landscape of both model development innovation, external environment and heightened regulatory expectations.


  • 0-2 years experience in analytics or big data workstreams
  • masters degree in economics, Statistics or Related Fields from Top Tier Institute
    Hands-on model development or validation experience
  • Strong Analytical and Relationship and project management skills for driving validation initiatives
  • Experience in applying advanced statistical and/or quantitative techniques to solve business problems is preferred
  • Good Verbal, Written, Interpersonal skills and ability to work effectively in a team environment
  • Willingness to Collaborate with Cross-Functional teams to drive validation and Project Execution
  • Effectively communicating complex Analytical results to Business Partners and Senior Management
  • Flexibility and Adaptability to Work Within tight deadlines and changing priorities
  • Experience with at least one of the data manipulation tools such as Python, Py Spark etc is a must have
  • Data Science/Traditional Modeling, Machine Learning/ Artificial Intelligence, Expertise in Coding, Supervised and Unsupervised Techniques – active learning, transfer learning, neural models, decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, map reduce techniques, Random Forest, Gradient Boosting, Deep Learning, Text Mining Algorithms
  • Enterprise Leadership Behaviors Set The Agenda:
  • Define What Winning Looks Like, Put Enterprise Thinking First, Lead with an External Perspective
  • Bring Others with You: Build the Best Team, Seek & Provide Coaching Feedback, Make Collaboration Essential
  • Do It the Right Way: Communicate Frequently, Candidly & Clearly, Make Decisions Quickly & Effectively, Live the Blue Box Values, Great Leadership Demands Courage


  • Conduct independent oversight of enterprise-wide models with a focus on a variety of statistical and mathematical models developed and used in Finance, Treasury and Risk – Economic Capital models, IFRS9, CECL, and CCAR Stress Test models,
  • Conduct gap assessments and establish robust framework to strengthen model risk controls and meet heightened regulatory standards
  • Conduct research to explore opportunities to elevate model excellence and drive business impact
  • Communicating results to partners, senior leadership and various model committees
    Business Outcomes:
  • Effectively challenge the conceptual soundness, theory and approach, purpose/usages of predictive models
  • Maximize business returns by institutionalizing efficient and accurate models.
  • Innovate modeling techniques and variable creation
  • Ensure modeling accuracy and enhance modeling efficiency in existing processes
  • Leadership Outcomes:
  • Put enterprise thinking first, connect the role s agenda to enterprise priorities and balance the needs of customers, partners, colleagues & shareholders.
  • Lead with an external perspective, challenge status quo and bring continuous innovation to the existing models
  • Demonstrate learning agility, make decisions quickly and with the highest level of integrity
  • Lead with a digital mindset and deliver the world s best customer experiences every day

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