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$119,050–$181,260.
Based on 240 similar postings.
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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 Senior Associate, Quantitative Analyst - Commercial Credit Modeling Team joins the Commercial Bank Team to manage a diverse loan portfolio including C&I, CRE, and Structured Products. In this role, you will develop credit risk models for internal risk rating, loss forecasting, stress testing, and pricing. You will build cloud-based solutions for model deployment and monitoring while applying quantitative methods to improve process efficiencies. Key responsibilities include using statistical techniques to predict credit risk loss across multi-million record datasets and blending business thinking with simulation tools to forecast rare events. Required skills include expertise in Python, R, and SQL, along with experience in linear and logistic regression, machine learning, time-series analysis, and survival analysis. You must demonstrate the ability to translate complex statistical concepts for non-statistical audiences.
Develop credit risk models for internal risk rating, loss forecasting, stress testing, and pricing.
Use statistical techniques and machine learning to predict credit risk loss across multi-million record datasets.
Apply simulation and quantitative tools to forecast rare or unprecedented financial events.
Build cloud-based solutions for model deployment, monitoring, and maintenance with data infrastructure teams.
Identify opportunities to apply quantitative methods and automation to improve model performance and process efficiencies.
Provide comprehensive support for model governance to ensure compliance with challenge functions.
Create accurate, efficient, and organized code using Python or R to solve complex business problems.
Maintain high-quality and transparent model documentation for all quantitative analysis.
What we're looking for
Must have a Master’s degree in a quantitative field or an MBA with a quantitative concentration plus 1 year of experience in quantitative analytics.
Must have at least 1 year of experience in statistical or econometric modeling and linear and logistic regression.
Must have at least 1 year of experience in programming with R, Python, or SQL.
Must have at least 1 year of experience presenting statistical concepts and research results to a non-statistical audience.
Must have at least 1 year of experience in at least 3 of the following: survival analysis, time-series, panel data, cross-sectional data, machine learning, or large dataset management.
Must possess excellent coding skills in Python and have a drive to create accurate, efficient, and organized code.
Must have a deep understanding of quantitative analysis methods within the context of financial institutions or commercial bank lending.
Must have 2 years of experience with Python, R, or other statistical analyst software (preferred).