Manager, Data Scientist, Marketing & Deposit Strategy

Capital One Financial

Confirmed live today High trust

Quick summary

Work type: On-site
Location: McLean, VA
Salary: $197,300–$225,100 / yr
Employment: Full-time
Posted: 2 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $194k

This role $211k

$158k $232k

below market most similar roles pay here above market

This role pays more than 65% of similar roles. Most pay $165,000–$223,562 — the blue band above. At the midpoint, this role pays about $211k versus about $194k 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, Marketing & Deposit Strategy

Role Posting Log in to save

Manager, Data Scientist - SBB Marketing & Deposit Strategy joins the Small Business Bank Data Science team to optimize financial products, policies, and services. In this role, you will partner with cross-functional teams of data scientists, software engineers, and product managers to deliver customer-facing products. You will build machine learning models through all phases of development, including design, training, evaluation, validation, and implementation. Specifically, you will develop account-level lifetime value models to forecast revenue and cost drivers for strategic decision-making. You will utilize a technical stack including Python, Conda, AWS, H2O, Spark, and relational databases to analyze large volumes of numeric and textual data. This position addresses the business problem of empowering small business entrepreneurs by leveraging statistics, machine learning, and emerging AI technologies to improve financial outcomes.

Skills

Python AWS Spark H2O Dask SQL Conda Machine Learning Statistical Modeling Relational Databases Big Data Data Science

What you'll do

Build machine learning models through all phases of development including design, training, evaluation, and implementation.
Develop account-level lifetime value (NPV) models to forecast revenue and cost drivers for strategic decision-making.
Leverage a broad technology stack including Python, AWS, H2O, and Spark to analyze large volumes of numeric and textual data.
Retrieve, combine, and analyze data from a variety of sources and structures to reveal hidden insights.
Translate complex technical work into tangible business goals for cross-functional stakeholders.
Research and evaluate emerging technologies and state-of-the-art methods to apply to business problems.

What we're looking for

Must have a Bachelor's in a quantitative field plus 6 years of data analytics experience, a Master's/MBA 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 hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
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, Dask, Spark, SQL, machine learning, and statistical modeling (preferred).

Save