This role pays less than
73%
of similar roles. Most pay
$145,200–$211,337
— the shaded band above.
At the midpoint, this role pays about
$145k
versus about
$178k
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
878 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 872 roles with salary data.
Senior Associate, Data Scientist - Credit Card Innovation joins the creditflow team to power next-generation credit decisioning and valuations model scoring platforms. In this role, you will build a robust scoring platform, deploy machine learning models through all phases of development, create innovative analytical tools, and leverage alternative data sources to optimize credit policy and enhance cash flow underwriting. You will collaborate cross-functionally with engineering and product teams to scale products and infrastructure. The work involves processing large volumes of numeric and textual data to provide real-time analytics for credit decisions. To succeed, you must utilize a technical stack including Python, Snowflake, Conda, AWS, H2O, Spark, and SQL. You will apply expertise in statistical modeling, clustering, classification, sentiment analysis, time series, and deep learning to solve complex problems within the credit infrastructure domain.
What does a Data Scientist earn in Virginia?
Median $145200 from 77 postings across 6 companies.
Build and deploy machine learning models through all phases of development including design, training, evaluation, and validation.
Develop a robust scoring platform to optimize credit policy and enhance cash flow underwriting.
Extract insights from large volumes of numeric and textual data using Python, Spark, and Snowflake.
Create innovative analytical tools and leverage alternative data sources for credit decisioning.
Translate complex technical findings into tangible business goals for cross-functional stakeholders.
Research and evaluate emerging technologies to improve existing machine learning models and infrastructure.
Manage the end-to-end lifecycle of data science solutions using cloud computing platforms like AWS.
What we're looking for
A Bachelor's degree in a quantitative field plus 2 years of experience performing data analytics.
A Master's degree in a quantitative field or an MBA with a quantitative concentration.
Experience building, validating, and backtesting machine learning models including clustering, classification, sentiment analysis, time series, and deep learning.
Proficiency in developing data science solutions using open-source tools and cloud computing platforms.
Ability to retrieve, combine, and analyze large volumes of numeric and textual data from various sources.
Experience working with AWS (preferred).
At least 2 years of experience in Python, Scala, or R (preferred).
At least 2 years of experience with machine learning and SQL (preferred).
Python
AWS
Machine Learning
Spark
H2O
SQL
Conda
Scala
R
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Big Data
Statistical Modeling
Python
Snowflake
AWS
Spark
H2O
OneLake
SQL
Conda
Scala
R
Machine Learning
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Data Analytics
Python
Snowflake
AWS
Spark
H2O
OneLake
SQL
Conda
Scala
R
Machine Learning
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Data Analytics
Python
AWS
Machine Learning
Spark
H2O
SQL
Conda
Scala
R
Deep Learning
Sentiment Analysis
Time Series
Clustering
Classification
Big Data
Statistical Modeling