Manager, Data Science, Business Intelligence

Capital One Financial

Confirmed live 2 days ago Trusted

Hybrid

Quick summary

Work type: Hybrid
Location: Houston, TXRichmond, VAMcLean, VAPlano, TX
Salary: $179,400–$204,700 / yr
Posted: 43 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $199k

This role $192k

$153k most similar roles pay here $244k

This role pays less than 54% of similar roles. Most pay $162,000–$235,487 — the shaded band above. At the midpoint, this role pays about $192k versus about $199k 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.

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View all roles at Capital One Financial

At a glance

TL;DR · Manager, Data Science, Business Intelligence

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Manager, Data Science - PULSE Network, Business Intelligence joins the PULSE Business Intelligence team to deliver data-driven insights for pricing, analytics, and relationship management. This role involves collaborating with cross-functional teams including finance and product groups to transform complex large data into actionable intelligence that optimizes pricing strategies, protects revenue, and improves overall business performance. The successful candidate will build machine learning models through all phases of development, from design and training to evaluation and implementation. To achieve these goals, the role utilizes a technical stack including Python, Conda, AWS, H2O, Spark, and relational databases. Key responsibilities involve performing advanced analytics and predictive modeling on large volumes of numeric and textual data. The work focuses on solving complex business problems by identifying hidden insights within massive datasets to drive strategic decision-making across the organization.

Skills

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

What you'll do

Deliver data-driven insights to support strategic decisions in pricing, analytics, and relationship management.
Develop machine learning models through all phases of development including design, training, evaluation, and implementation.
Use Python, Spark, and AWS to extract actionable intelligence from large volumes of numeric and textual data.
Partner with cross-functional teams of analysts and engineers to optimize revenue and business performance.
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 modeling capabilities.
Retrieve, combine, and analyze data from diverse sources and structures to solve undefined problems.

What we're looking for

A Bachelor's degree in a quantitative field plus 6 years of experience performing data analytics.
A Master's degree in a quantitative field or an MBA with a quantitative concentration plus 4 years of experience performing data analytics.
A PhD in a quantitative field plus 1 year of experience performing data analytics.
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.
At least 4 years of experience in Python, Scala, or R for large scale data analysis.
At least 4 years of experience with machine learning and statistical modeling techniques.

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