Piper Companies is seeking a Junior Data Scientist, to join one of the largest federal credit unions. The Junior Data Scientist will support risk modeling and credit policy development across various consumer banking products.
Responsibilities of the Junior Data Scientist include:
- Build machine learning models to support credit policy, risk mitigation, and marketing strategies across consumer banking products like credit cards, auto loans, and personal loans.
- Clean, merge, and transform large datasets from multiple sources, and engineer features to optimize model performance and accuracy.
- Analyze data to uncover trends, detect anomalies, and generate insights that inform model development and business decisions.
- Present findings and model insights to senior stakeholders and work closely with business and technical teams to ensure successful model implementation.
- Use statistical methods and machine learning algorithms (e.g., XGBoost, GLM) to enhance model robustness, address data imbalances, and validate credit risk and fraud models.
Qualifications for the Junior Data Scientist include:
- 3+ years of experience in the banking, credit union, FinTech, or insurance industries, with hands-on involvement in modeling for credit policy and risk mitigation.
- Strong technical skills in data manipulation, analysis, and model development using these core tools.
- Experience with predictive modeling, feature engineering, and statistical techniques, particularly in underwriting or customer management for credit products.
- Ability to clean, merge, and analyze high-volume, multi-source data to support model development and business insights.
- Capable of presenting data-driven insights to stakeholders and working cross-functionally to implement models and align with business goal
Compensation for the Junior Data Scientist include:
- Salary: $90,000 - $100,000
- Comprehensive Benefits: Medical, Dental, Vision, 401K, PTO, Sick Leave as required by law, and Holidays
This job opens for applications on June 4, 2025. Applications for this job will be accepted for at least 30 days from the posting date.
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Keywords: Python, SQL, machine learning, predictive modeling, credit risk, data analysis, feature engineering, data cleaning, exploratory data analysis (EDA), XGBoost, GLM, SMOTE, VIF, imputation, banking, FinTech, credit policy, risk mitigation, customer management, underwriting, data integration, statistical analysis, AUC, model validation, campaign optimization, data visualization, cross-functional collaboration, decision science, consumer banking, auto loans, credit cards, personal loans, checking accounts, savings accounts
