below marketmost similar roles pay hereabove market
This role pays more than
53%
of similar roles. Most pay
$162,000–$214,600
— the blue band above.
At the midpoint, this role pays about
$192k
versus about
$188k
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.
The Manager, Data Scientist - Credit Review joins the Credit Review Models, Data and Innovative solutions team to defend the company against model failures and improve decision-making. In this role, you will build statistical and machine learning models to challenge production models and reveal insights within massive volumes of numeric and textual data. You will partner with cross-functional teams of data scientists, credit risk experts, and product managers to deliver products that impact the bottom line. The position requires proficiency with a broad technology stack including Python, Conda, AWS, H2O, Spark, and relational databases. Key technical competencies include clustering, classification, sentiment analysis, time series, and deep learning. You will apply these skills to solve complex problems within the credit risk management and enterprise risk domains.
Use Python, AWS, H2O, and Spark to extract insights from large volumes of numeric and textual data.
Build statistical and machine learning models to challenge and validate existing production models.
Translate complex technical findings into tangible business goals for non-technical stakeholders.
Partner with cross-functional teams of data scientists and risk experts to deliver customer-facing products.
Research and evaluate emerging technologies and state-of-the-art methods to improve model performance.
Develop data science solutions using open-source tools and cloud computing platforms.
Perform model validation and backtesting using metrics like confusion matrices and ROC curves.
What we're looking for
Must have a Bachelor's in a quantitative field plus 6 years of data analytics experience, a Master's plus 4 years, or a PhD plus 1 year.
Must have at least 1 year of experience leveraging open source programming languages for large scale data analysis.
Must have at least 1 year of experience working with machine learning.
Must have at least 1 year of experience utilizing relational databases.
Must have experience building, validating, and backtesting models including clustering, classification, sentiment analysis, time series, and deep learning.
Must be able to leverage a tech stack including Python, Conda, AWS, H2O, and Spark.
PhD in a STEM field plus 3 years of experience in data analytics (preferred).
At least 4 years of experience in Python, Scala, or R for large scale data analysis (preferred).
Python
AWS
Spark
H2O
SQL
Scala
R
Conda
Relational Databases
Machine Learning
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Big Data
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
SQL
Scala
R
Conda
Relational Databases
Machine Learning
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Big Data
Python
AWS
Spark
H2O
SQL
Scala
R
Conda
Machine Learning
Relational Databases
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Statistical Modeling
Big Data