Senior Manager, Data Scientist, Card Fraud Prevention

Capital One Financial

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: McLean, VANew York, NY
Salary: $229,900–$262,400 / yr
Posted: 31 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $192k

This role $246k

$138k most similar roles pay here $276k

This role pays more than 87% of similar roles. Most pay $159,750–$223,750 — the shaded band above. At the midpoint, this role pays about $246k versus about $192k 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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Manager, Data Scientist, Card Fraud Prevention

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As a Senior Manager, Data Scientist - Card Fraud Prevention, you will join the Card Fraud Prevention data science team to detect and mitigate fraud by building and deploying machine learning models that keep customer accounts safe and compliant. You will partner with cross-functional teams of data scientists, software engineers, and product managers to develop production-ready insights from large volumes of numeric and textual data. The role involves managing all phases of model development, including design, training, evaluation, validation, and implementation. To succeed, you will utilize a modern tech stack featuring Python, Spark, Ray, H2O, PyTorch, Kubernetes, Conda, and AWS. You will apply expertise in traditional machine learning, deep learning, clustering, classification, sentiment analysis, and time series to solve complex problems involving large-scale data analysis and relational databases within the credit card industry.

Skills

Python Spark Ray H2O PyTorch Kubernetes AWS Conda Scala R Machine Learning Deep Learning Relational Databases Big Data Time Series Sentiment Analysis Clustering Classification

What you'll do

Build and deploy machine learning models to detect and mitigate fraud for customer accounts.
Develop production-ready insights using a tech stack including Python, Spark, H2O, and PyTorch.
Manage the full lifecycle of model development from design and training through evaluation and implementation.
Analyze large volumes of numeric and textual data to uncover hidden insights.
Translate complex technical findings into tangible business goals for stakeholders.
Research and evaluate emerging technologies and state-of-the-art methods to improve existing systems.
Retrieve, combine, and analyze data from diverse sources and structures.

What we're looking for

A Bachelor's degree in a quantitative field plus 7 years of experience performing data analytics.
A Master's degree in a quantitative field or an MBA with a quantitative concentration plus 5 years of experience performing data analytics.
A PhD in a quantitative field plus 2 years of experience performing data analytics.
At least 2 years of experience leveraging open source programming languages for large scale data analysis.
At least 2 years of experience working with machine learning.
At least 2 years of experience utilizing relational databases.
A PhD in a STEM field plus 4 years of experience in data analytics (preferred).
Experience with AWS, managing people, or 5+ years of experience in Python, Scala, or R and machine learning (preferred).

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