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.
Read the full posting
What you’ll work on
Full postingReview 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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- Live
- First seen by us
- Aug 21, 2026 · 61 days ago
- Recorded sightings
- 265
- Last seen by us
- Oct 21, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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Job description
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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- Pay
No pay amount identified in the saved description.
- Location & working pattern
New York, NY, United States
Working pattern and location restrictions need checking in the full posting.
- 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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