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Sr Data Scientist, NPV Modeling

Job in McLean, Fairfax County, Virginia, USA
Listing for: PenFed Credit Union
Full Time position
Listed on 2026-01-12
Job specializations:
  • Finance & Banking
    Data Scientist
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below

Overview

Pen Fed is hiring a (Hybrid) Sr Data Scientist - NPV Modeling at our Tysons, Virginia location. The primary purpose of this job will be to develop, maintain, and enhance Auto or Personal Loan Net Present Value (NPV) calculator using predictive models and analytics solutions that enhance our understanding of lifetime value. This role will also support the official, first-line loss forecast for Auto portfolio.

This role will work closely with both the consumer credit policy team and the credit risk management teams which will use the models to support credit decisioning, pricing, engagement and other business strategies for millions of Pen Fed members, positively impacting Pen Fed's financial performance.

Responsibilities

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This is not intended to be an all-inclusive list of job duties and the position will perform other duties as assigned.

  • Lead interaction with and advising Management of regarding credit risk issues; formulates product strategy recommendations and evaluates the risk in the overall loan portfolio.
  • Conduct autonomous end-to-end more complex statistical model creation, including but not limited to identifying objectives, compiling data, sampling/prepping data, feature selection, model comparison/selection, deployment, and monitoring.
  • Ensures adequate internal control processes around model development, implementation and validation are established.
  • Develop, monitor, and maintain risk models using advanced machine learning and statistical method.
  • Research and recommend new approaches/algorithms to identify relationships among complex data and implements model changes to improve model performance.
  • Understand the trends within consumer and commercial loans portfolio, their impact on model implementation design and performance, and develop timely approach to address changes.
  • Develop necessary analytics and processes during model implementation and forecasting process to provide production support and resolution.
  • Establish consistent and robust model implementation processes across models with effective review and controls.
  • Communicate design and results of model’s development and implementation to a variety of audiences, including senior management, bank supervisors, internal validation, Internal Audit and line of business credit and finance end users.
  • Apply intermediate to advanced knowledge of financial processes and procedures, and routine modeling theories and techniques to create effective modeling solutions for a single or multiple business functions.
  • Maintain documentation for key processes and model components across the team with focus on standardization of processes.
  • Engage model development teams, model production, and forecasting/model production team/users to develop consistent model implementation and process capabilities.
  • Participate in regular interactions with various stakeholders to enhance model implementation processes and translate requirements into integrated forecasting process/tools for effective consumption.
Qualifications

Equivalent combination of education and experience is considered.

  • Master’s Degree in quantitative discipline is required. PhD is highly preferred.
  • Minimum of three (3) years of related work experience in building statistical models and advanced data analysis. Minimum of one (1) years of experience for PhD degree holders.
  • Applied experience with Logistic Regression, Linear Regression, Machine Learning, and Survival Analysis required.
  • Advanced programming skills to include knowledge of statistical programs (e.g. SQL, Python, and R) required.
  • Ability to manage multiple projects simultaneously and implement rapid changes in project direction.
  • Demonstrate strong data analysis skills, ability to understand underlying data and complex loss/balance forecasting models, various product features, possess organizational and prioritization skills, as well as strong attention to detail.
  • Detail oriented, results driven, and the ability to navigate in a quickly changing and high demand environment to develop solutions while balancing multiple priorities.
  • Criti…
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