Piper Companies is seeking a Jr. Data Scientist to join one of the nation's largest premier credit unions based out of Mclean,VA . The Data Scientist will implement quantitative models to analyze credit and prepayment risk, determine the allowance for loan losses, and support financial planning. This role on-site 3 days per week in Mclean, VA)!

Responsibilities of the Jr. Data Scientist include:

• Implement models for loan loss allowance, CECL, stress testing, new volume origination, line of credit utilization, and prepayment models for all products, including credit card, personal loan, student loan, auto loan, mortgage, and commercial loan.
• Maintaining documentation for key processes and model components across the team with a focus on standardization of processes that satisfy model risk management, audit, and regulatory requirements.
• Implement vendor-developed models for consumer and commercial credit loss or prepayment.
• Monitor performance of quantitative models and support independent model validation efforts in accordance with the model risk management policy.
• Establish and document model implementation controls that satisfy model risk management, audit, and regulatory requirements.

Qualifications for the Jr. Data Scientist include:

• 3+ years of experience in quantitative modeling, development, or implementation.
• Working experience in data manipulation and advanced data analysis.
• Experience with SAS, R, Python, and proficiency working with large datasets is required.
• Applied experience with Logistic Regression, Linear Regression, Survival Analysis, Time Series Analysis, Decision Trees, and Cluster Analysis.
• Experience in at least one (1) of the following areas is preferred; real estate products, auto, credit card, student loan, or commercial loan.

Compensation for the Jr. Data Scientist include:

• Hourly Pay: $40 - $45/hr Salary Range: $90,000-$110,000 depending on experience
• Full benefits: PTO, Paid Holidays, Cigna Healthcare, Dental, Vision, 401k with ADPTS

Keywords: #LI-MM1 #LI-ONSITE

Data, data science, R, sas, python, datasets, logistic regression, linear regression, survival analysis, time series analysis, decision trees, cluster analysis, real estate, auto, credit card, consumer lending, consumer banking, modeling, model implementation, model risk, documentation, prepayment risk, financial services,