This role pays more than
92%
of similar roles. Most pay
$174,250–$246,150
— the shaded band above.
At the midpoint, this role pays about
$289k
versus about
$210k
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
1554 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 796 roles with salary data.
Senior Director, Data Scientist - Global Payment Network joins the Global Payment Network Data Solutions and Modeling team to build machine learning and AI agents that drive scalable intelligence across the payments ecosystem. This role involves partnering with cross-functional teams of data scientists, software engineers, and product managers to develop tools supporting fraud risk, merchant acceptance, and monitoring. The successful candidate will manage the full lifecycle of machine learning models, from design through training, evaluation, validation, and implementation. To uncover insights within large volumes of numeric and textual data, the role utilizes a technical stack including Python, Conda, AWS, H2O, Spark, Scala, and R. The position focuses on solving complex problems in the payments sector by creating automated intelligence to power smarter business decisions and provide value across various merchant and transaction monitoring systems.
Build machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
Utilize a broad technology stack including Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data.
Develop machine learning and AI agents to drive scalable intelligence for fraud, risk, and merchant monitoring.
Translate complex technical work into tangible business goals for stakeholders.
Research and evaluate emerging technologies and state-of-the-art methods to improve existing systems.
Solve large, undefined problems by identifying and improving the status quo through innovative data science solutions.
Mentor and develop talent within the team and across the organization.
What we're looking for
A Bachelor's degree in a quantitative field plus 11 years of experience performing data analytics.
A Master's degree in a quantitative field or an MBA with a quantitative concentration plus 9 years of experience performing data analytics.
A PhD in a quantitative field plus 6 years of experience performing data analytics.
At least 6 years of experience leveraging open source programming languages for large scale data analysis.
At least 6 years of experience working with machine learning.
At least 6 years of experience utilizing relational databases.
Extensive multi-project experience leading data science solutions within payments, financial services, or fintech sectors (preferred).
At least 1 year of experience working with AWS; at least 4 years managing people; and at least 6 years of experience in Python, Scala, or R (preferred).
Python
AWS
H2O
Spark
Conda
Machine Learning
Relational Databases
Scala
R
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Big Data
Statistics
Python
Snowflake
Conda
AWS
H2O
Spark
SQL
Machine Learning
Statistical Modeling
Scala
R
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Big Data
Cloud Computing
Python
AWS
Spark
H2O
Conda
Machine Learning
Scala
R
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Relational Databases
Big Data