Counterparty Risk Analyst
The Counterparty Risk Analyst leverages data to identify, assess, and mitigate risk across borrowers, dealers, and lending channels. This role combines SQL and Python-based analysis with data visualization and modeling techniques to uncover fraud, detect anomalies, and support underwriting and dealer monitoring strategies. The ideal candidate is a curious, analytical problem-solver who can connect complex datasets, translate insights into actionable recommendations, and help drive informed, data-driven risk decisions.
Essential Functions
Write and maintain SQL queries to extract, transform, and analyze structured datasets (and semi-structured data where applicable).
Develop SQL and Python (pandas, NumPy) scripts for data processing, feature engineering, and model experimentation.
Integrate and analyze data across borrowers, applications, loans, dealerships, and sales channels to identify risk patterns.
Detect fraud, potential fraud, and anomalous activity across borrower and dealer populations.
Design, test, and refine risk rules and predictive models to support underwriting, fraud detection, and dealer monitoring.
Build dashboards and visualizations (e.g., heatmaps, Sankey diagrams) using tools such as Power BI, Tableau, Sigma, or Streamlit to communicate insights and recommendations.
Translate data findings into actionable insights that improve risk decisions and reduce losses.
Required Education and Experience
Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field, or commensurate work experience, is required
5 years of experience with SQL and relational databases, required
5 years of experience using Python for data analysis (pandas, NumPy, or similar, required
Experience building dashboards or data visualizations using BI tools (Power BI, Tableau, Sigma, Streamlit, or similar).
Exposure to machine learning concepts and modeling techniques (e.g., Logistic Regression, Random Forest, XGBoost).
Familiarity with version control tools (e.g., Git).
Strong problem-solving skills and ability to learn quickly.
Financial services or lending experience preferred.
Experience with Snowflake or similar cloud data platforms preferred.
Physical Demands
While performing the duties of this job, the employee is frequently required to sit, stand, walk, visualize, talk, hear, and handle or touch objects or controls. The employee may occasionally lift, push, or pull up to 20 pounds.
This position is an office-based position where you must be able to sit for long periods of time. The employee will be working on a computer 90% of the time.
Apply To This Job
Essential Functions
Write and maintain SQL queries to extract, transform, and analyze structured datasets (and semi-structured data where applicable).
Develop SQL and Python (pandas, NumPy) scripts for data processing, feature engineering, and model experimentation.
Integrate and analyze data across borrowers, applications, loans, dealerships, and sales channels to identify risk patterns.
Detect fraud, potential fraud, and anomalous activity across borrower and dealer populations.
Design, test, and refine risk rules and predictive models to support underwriting, fraud detection, and dealer monitoring.
Build dashboards and visualizations (e.g., heatmaps, Sankey diagrams) using tools such as Power BI, Tableau, Sigma, or Streamlit to communicate insights and recommendations.
Translate data findings into actionable insights that improve risk decisions and reduce losses.
Required Education and Experience
Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field, or commensurate work experience, is required
5 years of experience with SQL and relational databases, required
5 years of experience using Python for data analysis (pandas, NumPy, or similar, required
Experience building dashboards or data visualizations using BI tools (Power BI, Tableau, Sigma, Streamlit, or similar).
Exposure to machine learning concepts and modeling techniques (e.g., Logistic Regression, Random Forest, XGBoost).
Familiarity with version control tools (e.g., Git).
Strong problem-solving skills and ability to learn quickly.
Financial services or lending experience preferred.
Experience with Snowflake or similar cloud data platforms preferred.
Physical Demands
While performing the duties of this job, the employee is frequently required to sit, stand, walk, visualize, talk, hear, and handle or touch objects or controls. The employee may occasionally lift, push, or pull up to 20 pounds.
This position is an office-based position where you must be able to sit for long periods of time. The employee will be working on a computer 90% of the time.
Apply To This Job