Senior Manager, Data Science, Bank Operations

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: McLean, VANew York, NY
Salary: $229,900–$262,400 / yr
Posted: 59 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 $189k

This role $246k

$131k most similar roles pay here $277k

This role pays more than 88% of similar roles. Most pay $162,000–$216,681 — the shaded band above. At the midpoint, this role pays about $246k versus about $189k 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 Science, Bank Operations

Role Posting Log in to save

Senior Manager, Data Science, Bank Operations joins the Bank Operations Data Science team to build machine learning models supporting core internal capabilities such as Check/Document Reading, Anomaly Identification, Natural Language Processing of Calls, and operational forecasting. In this role, you will partner with cross-functional teams of data scientists, software engineers, and product managers to develop products by building machine learning models through all phases of development, from design and training to evaluation and implementation. You will utilize a technical stack including Python, Conda, AWS, H2O, Spark, and relational databases to uncover insights within large volumes of numeric and textual data. The work involves leveraging emerging technologies like neural networks, LLMs, transformer architectures, and agentic experiences to solve complex problems in the domain of bank operations and automated internal processes.

Skills

Machine Learning Python AWS Spark H2O Conda Scala R LLMs Transformer Architectures Neural Networks Natural Language Processing Relational Databases Cloud Computing

What you'll do

Build machine learning models for check reading, anomaly identification, NLP of calls, and operational forecasting.
Develop advanced models using neural networks, LLMs, transformer architectures, and agentic experiences.
Utilize Python, Spark, AWS, and H2O to extract insights from large volumes of numeric and textual data.
Manage the full machine learning lifecycle including design, training, evaluation, validation, and implementation.
Translate complex technical findings into tangible business goals for non-technical stakeholders.
Research and evaluate emerging technologies to improve current state-of-the-art methods and applications.
Solve large, undefined problems by identifying and improving existing processes and status quo.

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.
At least 1 year of experience working with AWS.
At least 1 year of experience managing people.

Save