Manager, Data Science, Business Intelligence

Capital One Financial

Confirmed live today Low trust
Hybrid

Quick summary

Work type
Hybrid
Location
Houston, TXRichmond, VAMcLean, VAPlano, TX
Employment
Full-time
Posted
88 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $196k
$156k $237k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $167,700–$223,887.

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.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Manager, Data Science, Business Intelligence

Role Posting Log in to save

Manager, Data Science - PULSE Network, Business Intelligence joins the PULSE Business Intelligence team to deliver data-driven insights for strategic business decisions. You will partner with cross-functional teams including pricing, analytics, and finance to optimize revenue and improve business performance. Your daily responsibilities involve building machine learning models through all phases of development, from design and training to evaluation and implementation. You will analyze huge volumes of numeric and textual data to support pricing strategies and protect revenue. The role requires proficiency with a technology stack including Python, Conda, AWS, H2O, Spark, and relational databases. You must apply skills in clustering, classification, sentiment analysis, time series, and deep learning to transform complex large data into actionable intelligence within a large-scale transaction dataset environment.

What does a Data Science Manager earn?

Median $211200 from 43 postings across 13 companies.

See salary data

Skills

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

What you'll do

  • Deliver data-driven insights to support strategic business decisions for pricing, analytics, and finance teams.
  • Optimize revenue by partnering with cross-functional teams of analysts and data engineers.
  • Use Python, AWS, H2O, and Spark to extract insights from large volumes of numeric and textual data.
  • Build machine learning models through all phases of development, including design, training, evaluation, and implementation.
  • Translate complex technical work into tangible business goals for non-technical stakeholders.
  • Research and evaluate emerging technologies and state-of-the-art methods to apply to business problems.
  • Retrieve, combine, and analyze data from a variety of sources and structures to solve undefined problems.

What we're looking for

  • A Bachelor's degree in a quantitative field plus 6 years of data analytics experience.
  • A Master's degree in a quantitative field or MBA with a quantitative concentration plus 4 years of data analytics experience.
  • A PhD in a quantitative field plus 1 year of data analytics experience.
  • At least 1 year of experience leveraging open source programming languages for large scale data analysis.
  • At least 1 year of experience working with machine learning.
  • At least 1 year of experience utilizing relational databases.
  • PhD in a STEM field plus 3 years of experience in data analytics (preferred).
  • At least 1 year of experience working with AWS (preferred).
  • At least 4 years of experience in Python, Scala, or R for large scale data analysis (preferred).
  • At least 4 years of experience with machine learning and statistical modeling techniques (preferred).
  • At least 4 years of experience with SQL (preferred).
  • Experience with large-scale transaction datasets (preferred).

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