Senior Manager, Data Science, Business Card and Payment

Capital One Financial

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: McLean, VA
Salary: $229,900–$262,400 / yr
Employment: Full-time
Posted: 8 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $188k

This role $246k

$133k $276k

below market most similar roles pay here above market

This role pays more than 91% of similar roles. Most pay $162,000–$214,900 — the blue band above. At the midpoint, this role pays about $246k versus about $188k 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 2105 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1121 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Manager, Data Science, Business Card and Payment

Role Posting Log in to save

The Senior Manager, Data Science - Business Card and Payment joins the Business Cards & Payments Credit Infrastructure team to inform underwriting and marketing decisions for flagship small business card products. In this role, you will partner with data scientists, software engineers, and product managers to build novel decision systems and machine learning models through all phases of development, including design, training, evaluation, validation, and implementation. You will leverage a broad technology stack including Python, Conda, AWS, H2O, Spark, and relational databases to extract insights from massive volumes of numeric and textual data. Key technical competencies include clustering, classification, sentiment analysis, time series, and deep learning. You will translate complex statistical analysis into tangible business goals to solve problems within the credit infrastructure domain.

What does a Data Science Manager earn?

Median $211200 from 43 postings across 13 companies.

See salary data

Skills

Python AWS Spark H2O Conda Scala R Machine Learning Relational Databases Deep Learning Time Series Sentiment Analysis Clustering Classification Causal Inference Econometrics Statistical Modeling

What you'll do

Build machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
Conduct rigorous statistical analysis to inform underwriting and marketing decisions for small business card products.
Leverage a broad technology stack including Python, AWS, H2O, and Spark to analyze large volumes of numeric and textual data.
Translate complex technical work into tangible business goals for stakeholders.
Develop novel decision systems to improve the status quo of credit infrastructure.
Research and evaluate emerging technologies and state-of-the-art methods for application in data science.
Manage and develop talent for the data science team.

What we're looking for

Must have a Bachelor's in a quantitative field plus 7 years of data analytics experience.
Must have a Master's in a quantitative field or MBA with a quantitative concentration plus 5 years of data analytics experience.
Must have a PhD in a quantitative field plus 2 years of data analytics experience.
Must have at least 2 years of experience leveraging open source programming languages for large scale data analysis.
Must have at least 2 years of experience working with machine learning.
Must have 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 (preferred).
At least 1 year of experience managing people (preferred).
At least 5 years’ experience in Python, Scala, or R for large scale data analysis (preferred).
At least 5 years’ experience with econometrics or causal inference (preferred).
At least 5 years’ experience with machine learning, specifically reinforcement learning (preferred).

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