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Manager, Data Science

New York, NY, United States

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

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
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What you’ll work on

Full posting
  • Review credit risk, fraud risk, and line management models for soundness, data quality, and performance

  • Write detailed model review reports and prepare for regulatory and internal audit reviews

  • Communicate model review results to business partners, senior leaders, and regulators

  • Evaluate machine learning algorithms and how they are applied in models

  • Enhance the governance framework for evolving modeling techniques and model risk management

From the employer’s posting
Oversee credit risk, fraud risk, and line management models which include evaluating conceptual soundness, data quality, performance validation, and on-going monitoring
Document detailed model review reports and prepare for regulatory and internal audit reviews
Communicate model review results to business partners, senior leaders, and regulators
Evaluate machine learning algorithms and their application on models
Enhance governance framework to accommodate the evolving modeling techniques, model development, as well as model risk management

Tools in this posting

  • C++
  • Java
  • Python
  • R
  • Scala
  • AWS
  • Hadoop
  • Hive
  • Spark
  • XGBoost
Source — Tool mentions in context
- Experience in large data processing and handling is a plus—familiarity with big data platforms and applications, such as Hadoop, Pig, Hive, Spark, AWS. - Must be skilled in coding using Python/R; additionally, Java, Scala, and C++ a plus. - Strong communication and written skills
- The qualified candidate should have a good understanding of machine learning algorithms (e.g., gradient boosting machine, XGBoost, neural network), artificial intelligence, deep learning as well as classic statistical modeling techniques and assumptions. - Experience in large data processing and handling is a plus—familiarity with big data platforms and applications, such as Hadoop, Pig, Hive, Spark, AWS. - Must be skilled in coding using Python/R; additionally, Java, Scala, and C++ a plus.
- Hands-on modeling experience is preferred - The qualified candidate should have a good understanding of machine learning algorithms (e.g., gradient boosting machine, XGBoost, neural network), artificial intelligence, deep learning as well as classic statistical modeling techniques and assumptions. - Experience in large data processing and handling is a plus—familiarity with big data platforms and applications, such as Hadoop, Pig, Hive, Spark, AWS.

Posting record

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Status in our records
Live
First seen by us
Aug 21, 2026 · 61 days ago
Recorded sightings
265
Last seen by us
Oct 21, 2026

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Job description

View original posting ↗

The Model Risk Management Group (MRMG) is responsible for oversight of model risk and governance over machine learning usage enterprise wide. The role will be primarily responsible for the review of credit risk, fraud risk, and line management models. The responsibilities of the individual are also to ensure that there is an elevation of modeling as well as fulfilling regulatory requirements for model risk management. This is a highly competitive role and one that ensures the individual achieves maximum potential intellectually as well as for the company.

This role will report to a director in MRMG. The specific responsibilities include:

  • Oversee credit risk, fraud risk, and line management models which include evaluating conceptual soundness, data quality, performance validation, and on-going monitoring
  • Document detailed model review reports and prepare for regulatory and internal audit reviews
  • Communicate model review results to business partners, senior leaders, and regulators
  • Evaluate machine learning algorithms and their application on models
  • Enhance governance framework to accommodate the evolving modeling techniques, model development, as well as model risk management

 

  • Advanced degree in quantitative fields
  • Hands-on modeling experience is preferred
  • The qualified candidate should have a good understanding of machine learning algorithms (e.g.,     gradient boosting machine, XGBoost, neural network), artificial intelligence, deep learning as well   as classic statistical modeling techniques and assumptions.
  • Experience in large data processing and handling is a plus—familiarity with big data platforms and   applications, such as Hadoop, Pig, Hive, Spark, AWS.
  • Must be skilled in coding using Python/R; additionally, Java, Scala, and C++ a plus.
  • Strong communication and written skills
  • Flexibility and adaptability to work within tight deadlines and changing priorities

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions. 

Source details

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Location & working pattern

New York, NY, United States

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Work authorization
- Flexibility and adaptability to work within tight deadlines and changing priorities Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.

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