Senior Director, Data Scientist

Capital One Financial

Confirmed live today High trust

Quick summary

Work type
On-site
Location
McLean, VANew York, NYCambridge, MA
Salary
$314,800–$359,300 / yr
Employment
Full-time
Posted
3 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $198k
This role $337k
$118k $385k
below market most similar roles pay here above market

This role pays more than 99% of similar roles. Most pay $162,000–$235,000 — the blue band above. At the midpoint, this role pays about $337k versus about $198k 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 2164 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1129 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Director, Data Scientist

Role Posting Log in to save

The Senior Director, Data Scientist - US Card joins the US Card Data Science organization to drive business strategy and deliver customer experiences. In this role, you will partner with cross-functional teams of data scientists, software engineers, and product managers to build and deploy sophisticated machine learning models across the entire credit card lifecycle, including marketing, acquisitions, underwriting, and fraud prevention. You will manage the full development lifecycle from design through training, evaluation, validation, and implementation. The position requires proficiency with Python, Conda, AWS, H2O, Spark, and relational databases to analyze huge volumes of numeric and textual data. You will apply skills in clustering, classification, sentiment analysis, time series, and deep learning to solve complex problems and turn data insights into tangible business goals for millions of cardholders.

Skills

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

What you'll do

  • Build machine learning models through all phases of development including design, training, evaluation, and implementation.
  • Leverage Python, Conda, AWS, H2O, and Spark to extract insights from large volumes of numeric and textual data.
  • Develop data science solutions for marketing, acquisitions, underwriting, and fraud prevention across the credit card lifecycle.
  • Translate complex technical work into tangible business goals for stakeholders and cross-functional teams.
  • Retrieve, combine, and analyze data from a variety of sources and structures to drive business strategy.
  • Research and evaluate emerging technologies and state-of-the-art methods to apply to company products.
  • Identify and improve the status quo by challenging conventional thinking and providing leadership for talent development.

What we're looking for

  • Must have a Bachelor's in a quantitative field plus 11 years of data analytics experience.
  • Must have a Master's in a quantitative field or MBA with a quantitative concentration plus 9 years of data analytics experience.
  • Must have a PhD in a quantitative field plus 6 years of data analytics experience.
  • Must have at least 6 years of experience leveraging open source programming languages for large scale data analysis.
  • Must have at least 6 years of experience working with machine learning.
  • Must have at least 6 years of experience utilizing relational databases.
  • PhD in a STEM field plus 7 years of experience in data analytics (preferred).
  • At least 1 year of experience working with AWS (preferred).
  • At least 4 years of experience managing people (preferred).
  • At least 6 years of experience in Python, Scala, or R for large scale data analysis (preferred).
  • At least 7 years of experience with machine learning (preferred).

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