below marketmost similar roles pay hereabove market
This role pays less than
63%
of similar roles. Most pay
$161,037–$233,137
— the blue band above.
At the midpoint, this role pays about
$173k
versus about
$197k
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
2107 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1107 roles with salary data.
As a Principal Associate, Data Scientist - Card Finance Innovation Team, you will join the Innovation team to power the core forecasting engine for Card Finance. You will spearhead the architectural design and deployment of a next-generation forecasting ecosystem to navigate monthly outlooks, annual budgets, and long-term strategic planning. Your daily responsibilities include building machine learning models through all phases of development, including training, evaluation, and validation, while partnering with cross-functional teams to translate complex data into tangible business goals. You will utilize a modern tech stack including Python, OneLake, Snowflake, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data. This role solves critical business problems by providing the data-driven insights necessary for accurate financial forecasting and strategic planning.
What does a Data Scientist earn in Virginia?
Median $162000 from 89 postings across 9 companies.
Spearhead the architectural design and deployment of a next-generation forecasting ecosystem.
Build machine learning models through all phases of development, including design, training, evaluation, and validation.
Leverage Python, AWS, Spark, and Snowflake to extract insights from large volumes of numeric and textual data.
Power the core forecasting engine to support monthly outlooks, annual budgets, and long-term strategic planning.
Translate complex technical work into tangible business goals for stakeholders.
Implement process automation and model risk governance to ensure operational excellence.
Analyze and interpret statistical metrics such as confusion matrices and ROC curves.
What we're looking for
Must have a Bachelor's degree in a quantitative field plus 5 years of data analytics experience.
Must have a Master's degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of data analytics experience.
Must have a PhD in a quantitative field.
Must have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Must have experience building, validating, and backtesting models including clustering, classification, sentiment analysis, time series, and deep learning.
Must have experience with Python, Conda, AWS, H2O, Spark, and Snowflake.
Must have at least 3 years of experience in Python, Scala, or R (preferred).
Must have at least 3 years of experience in machine learning and SQL (preferred).
Python
Snowflake
AWS
Spark
H2O
OneLake
SQL
Scala
R
Conda
Machine Learning
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Process Automation
Python
AWS
Spark
H2O
SQL
Scala
R
Conda
Machine Learning
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Big Data
Python
AWS
Spark
H2O
SQL
Scala
R
Conda
Machine Learning
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Big Data