below marketmost similar roles pay hereabove market
This role pays less than
66%
of similar roles. Most pay
$139,875–$211,750
— the blue band above.
At the midpoint, this role pays about
$145k
versus about
$176k
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
2229 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1126 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. This role involves building a robust scoring platform, deploying models, and creating innovative analytical tools while leveraging alternative data sources. You will collaborate cross-functionally with engineering and product teams to scale products and analytical capabilities. Day-to-day responsibilities include building machine learning models through all phases of development, from design to implementation, and revealing insights within huge volumes of numeric and textual data. The technical stack includes Python, Snowflake, Conda, AWS, H2O, Spark, Scala, and SQL. You will apply statistical modeling, clustering, classification, sentiment analysis, time series, and deep learning to optimize credit policy, enhance cash flow underwriting, and deliver lightning-fast credit decisions.
What does a Data Scientist earn in Virginia?
Median $162000 from 90 postings across 8 companies.
Build and deploy a robust scoring platform for credit decisioning and valuations.
Develop machine learning models through all phases of design, training, evaluation, and implementation.
Leverage Python, AWS, Spark, and Snowflake to extract insights from large volumes of numeric and textual data.
Integrate alternative data sources to enhance cash flow underwriting and credit policy optimization.
Translate complex technical work into tangible business goals for cross-functional stakeholders.
Research and evaluate emerging technologies and state-of-the-art methods to improve analytical capabilities.
Retrieve and combine data from various structures to support real-time analytics and credit infrastructure.
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.
Experience developing data science solutions using open-source tools and cloud computing platforms.
Proficiency in retrieving, combining, and analyzing data from a variety of sources and structures.
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 (preferred).
At least 2 years of experience with SQL (preferred).
Python
AWS
Spark
H2O
Scala
R
Machine Learning
Relational Databases
Conda
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Big Data
Python
AWS
Spark
H2O
Conda
Scala
R
Machine Learning
Relational Databases
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Big Data
Python
AWS
Spark
H2O
SQL
Scala
R
Machine Learning
Deep Learning
Conda
Statistical Modeling
Sentiment Analysis
Time Series
Clustering
Classification
Data Analytics