Senior Manager, Data Science, Bank Operations

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type
On-site
Location
McLean, VANew York, NY
Employment
Full-time
Posted
105 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $188k
$130k $237k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $162,000–$214,900.

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 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Senior Manager, Data Science, Bank Operations

Role Posting Log in to save

The Senior Manager, Data Science, Bank Operations joins the Bank Operations Data Science team to build machine learning models for core internal capabilities. You will partner with cross-functional teams of data scientists, software engineers, and product managers to deliver products by building models through all phases of development, including design, training, evaluation, validation, and implementation. You will utilize a broad technology stack including Python, Conda, AWS, H2O, Spark, and relational databases to reveal insights within huge volumes of numeric and textual data. The role involves developing neural networks, LLMs, transformer architectures, and agentic experiences to solve problems such as Check/Document Reading, Anomaly Identification, Natural Language Processing of Calls, and operational forecasting within a large-scale banking environment.

Skills

Python AWS Spark H2O Scala R Machine Learning LLMs Neural Networks Transformer Architectures Conda Relational Databases Natural Language Processing Statistical Modeling Data Analytics

What you'll do

  • Build machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
  • Leverage Python, Conda, AWS, H2O, and Spark to extract insights from large volumes of numeric and textual data.
  • Develop models for core capabilities such as Check/Document Reading, Anomaly Identification, and Natural Language Processing.
  • Research and evaluate emerging technologies like neural networks, LLMs, and transformer architectures for production use.
  • Translate complex technical work into tangible business goals for stakeholders.
  • Identify and improve the status quo by challenging conventional thinking and providing technical leadership.

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.
  • PhD in a STEM field plus 4 years of experience in data analytics (preferred).
  • At least 1 year of experience working with AWS, managing people, or 5 years of experience in Python, Scala, or R and machine learning (preferred).

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