Senior Manager, Data Science

Capital One Financial

Confirmed live 2 days ago Trusted

Quick summary

Work type
On-site
Location
Richmond, VANew York, NYMcLean, VA
Salary
$229,900–$262,400 / yr
Posted
9 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 $187k
This role $246k
$123k most similar roles pay here $277k

This role pays more than 90% of similar roles. Most pay $159,562–$213,942 — the shaded band above. At the midpoint, this role pays about $246k versus about $187k 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

Role Posting Log in to save

As a Senior Manager, Data Science - US Card (Upmarket Segments), you will join a team focused on leveraging advanced analytics to improve customer experiences in the credit card industry. You will partner with cross-functional teams of data scientists, software engineers, and product managers to build machine learning models through every phase of development, including design, training, evaluation, validation, and implementation. To uncover insights within massive volumes of numeric and textual data, you will utilize a technical stack featuring Python, Conda, AWS, H2O, Spark, and relational databases. The role requires expertise in clustering, classification, sentiment analysis, time series, and deep learning to solve complex problems involving billions of customer records. You must be able to translate technical complexities into tangible business goals while utilizing open-source tools and cloud computing platforms to drive data-driven decision-making.

Skills

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

What you'll do

  • Develop machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
  • Utilize a broad stack of technologies including Python, Conda, AWS, H2O, and Spark to analyze large volumes of data.
  • Extract insights from complex numeric and textual datasets to drive product improvements.
  • Translate complex technical findings into tangible business goals for non-technical stakeholders.
  • Research and evaluate emerging technologies and state-of-the-art methods to improve existing processes.
  • Solve large, undefined problems by identifying innovative ways to improve the status quo.
  • Manage and develop talent within the data science team.

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.
  • Experience building and validating models using techniques like clustering, classification, sentiment analysis, time series, and deep learning.
  • Proficiency in tools such as Python, Conda, AWS, H2O, and Spark to analyze large volumes of data.

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