Manager, Data Scientist, Financial Services, Pricing

Capital One Financial

Confirmed live today High trust

Quick summary

Work type: On-site
Location: Plano, TXMcLean, VA
Salary: $197,300–$225,100 / yr
Employment: Full-time
Posted: 9 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 $180k

This role $211k

$131k $235k

below market most similar roles pay here above market

This role pays more than 70% of similar roles. Most pay $141,000–$219,537 — the blue band above. At the midpoint, this role pays about $211k versus about $180k 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 2276 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1147 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Manager, Data Scientist, Financial Services, Pricing

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Manager, Data Scientist -Financial Services- Pricing joins a team focused on data-driven decision-making to unlock opportunities within billions of customer records. In this role, you will partner with cross-functional teams of data scientists, software engineers, and product managers to deliver customer-facing products. Your daily responsibilities include building 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 reveal insights within huge volumes of numeric and textual data. The work involves solving complex problems using clustering, classification, sentiment analysis, time series, and deep learning. You must translate technical complexity into tangible business goals while managing large-scale data analysis and cloud computing platforms.

Skills

Python AWS Spark SQL H2O Scala R Conda Relational Databases Machine Learning 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, validation, and implementation.
Leverage a broad technology stack including Python, AWS, H2O, and Spark to extract insights from large volumes of data.
Retrieve, combine, and analyze data from a variety of sources and structures to support data-driven decision-making.
Translate complex technical work into tangible business goals for stakeholders.
Research and evaluate emerging technologies and state-of-the-art methods to apply to company projects.
Identify and improve the status quo by challenging conventional thinking and working with stakeholders.
Develop and mentor talent for your own team and the broader organization.

What we're looking for

Must have a Bachelor's in a quantitative field plus 6 years of data analytics experience, a Master's plus 4 years, or a PhD plus 1 year.
Must have at least 1 year of experience leveraging open source programming languages for large scale data analysis.
Must have at least 1 year of experience working with machine learning.
Must have at least 1 year of experience utilizing relational databases.
Must have experience with clustering, classification, sentiment analysis, time series, and deep learning.
Must have experience building, validating, and backtesting models while interpreting confusion matrices or ROC curves.
Must have experience with AWS (preferred).
Must have at least 4 years of experience in Python, Scala, or R for large scale data analysis (preferred).

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