below marketmost similar roles pay hereabove market
This role pays less than
67%
of similar roles. Most pay
$173,200–$229,100
— the blue band above.
At the midpoint, this role pays about
$173k
versus about
$201k
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
2204 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1138 roles with salary data.
JOB TITLE: Principal Associate, Data Science - Model Risk Office
The Principal Associate, Data Science - Model Risk Office joins a team dedicated to defending the enterprise against model failures and improving decision-making. In this role, you will partner with data scientists, software engineers, and product managers to identify and quantify risks associated with models. You will build machine learning models to challenge production champion models, contribute to model governance frameworks, and validate various models across multiple business domains. Utilizing a technical stack including Python, Conda, AWS, Spark, Scala, R, and SQL, you will analyze large volumes of numeric and textual data. Key responsibilities involve performing clustering, classification, sentiment analysis, time series, and deep learning to provide insights and present risk impacts to executives within the Enterprise Services division.
Identify and quantify risks associated with models in partnership with cross-functional teams.
Use Python, Conda, AWS, and Spark to extract insights from large volumes of numeric and textual data.
Build machine learning models to challenge and test "champion models" currently deployed in production.
Contribute to the model governance framework for the next generation of machine learning models.
Present findings on how model risks could impact the business to executive leadership.
Validate a wide variety of models across multiple business domains within the Enterprise Services division.
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 be able to retrieve, combine, and analyze data from a variety of sources and structures.
Master’s degree in a STEM field plus 3 years of data analytics experience, or a PhD in a STEM field (preferred).
At least 1 year of AWS experience, 3 years of Python, Scala, or R experience, 3 years of machine learning experience, and 3 years of SQL experience (preferred).
Python
AWS
Spark
H2O
SQL
Scala
R
Conda
Machine Learning
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Big Data
Python
Scala
R
PyTorch
Hugging Face
LangChain
Vector Databases
LLMOps
AWS
Machine Learning
Deep Learning
Statistics
Time Series
Sentiment Analysis
Clustering
Classification
Python
AWS
Spark
H2O
SQL
Scala
R
NLP
Generative AI
Machine Learning
Conda
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
ROC Curve
Confusion Matrix
Machine Learning
Python
Scala
R
AWS
Relational Databases
Gradient Boosting
Deep Learning
Time Series
Clustering
Classification
Sentiment Analysis
Statistical Modeling
econometric, s
Big Data
ROC Curve
Confusion Matrix