Manager, Data Scientist - Card Payment Fraud Prevention

Capital One Financial

Quick summary

Work type
On-site
Location
McLean, VA · New York, NY · Chicago, IL
Salary
$179,400–$204,700 / yr
Posted
3 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $173k
This role $192k
$104k most similar roles pay here $232k

This role pays more than 68% of similar roles. Most pay $134,350–$211,200 — the shaded band above. At the midpoint, this role pays about $192k versus about $173k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 573 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 569 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Manager, Data Scientist - Card Payment Fraud Prevention

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As a Manager of Data Science on the Card Payment Fraud Prevention team, you will lead the development and deployment of advanced machine learning models to combat first-party fraud across billions of transactions. Your daily tasks include designing, training, evaluating, validating, and maintaining these models in production, ensuring they adhere to best practices and regulatory compliance. You will work with a cutting-edge tech stack that includes Python, Spark, Ray, H2O, PyTorch, and Kubernetes, optimizing models for challenging segments to enhance fraud detection rates and customer safety. Ideal candidates are experts in large-scale data analysis, machine learning model deployment, big data processing, and team leadership, with hands-on experience in traditional ML methodologies and a solid understanding of clustering, classification, time series analysis, and black box models like GBMs.

Skills

Python Spark Kubernetes H2O PyTorch Ray Machine Learning Clustering Classification Time Series GBMs Model Risk Governance CI/CD Big Data Distributed Computing

What you'll do

  • Lead the development and deployment of machine learning models to prevent card payment fraud.
  • Optimize and maintain machine learning models in production to enhance fraud detection rates.
  • Ensure compliance with regulatory standards throughout the model lifecycle.
  • Collaborate on designing and documenting data science solutions for production use.
  • Manage a team of data scientists, guiding technical leadership and development.
  • Conduct independent model validation and risk assessments to ensure reliability.

What we're looking for

  • At least 4 years of experience in Python for large-scale data analysis.
  • Proven track record of developing and deploying machine learning models in production.
  • Experience with big data and distributed computing using frameworks like Spark.
  • Demonstrated expertise in model risk governance throughout the model lifecycle.
  • Hands-on experience leading and developing a technical team in data science.
  • Strong background in traditional machine learning methodologies, including black box models.

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