• Risk Engineering | Retail Loss Forecasting - Vice President

    Location(s) US-TX-Dallas
    Job ID
    Schedule Type
    Full Time
    Vice President/Executive Director
    Engineering, Technology
    Business Unit
    Risk Engineering
    Employment Type



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    Job Summary


    We are seeking a VP level candidate to join the Risk Engineering team focusing on Loss Forecasting process for unsecured consumer lending assets.  This position will be responsible for delivering analytical support for Loss Forecasting activities, typical responsibilities and duties include the following:

    • Partner with business units and broader Credit department to assess data availability, data sufficiency, and appropriate modelling approaches. (all encompassing)
    • Specifically, responsible for managing Model risk of Loss Forecasting models for the unsecured consumer lending products. In this role, the successful candidate will interact with model developers, model risk governance group, business risk teams, internal audit, and regulatory agencies when required.
    • Leverages business/ product expertise to evaluate/ effectively challenge the credit loss assumptions for benign and stress case scenarios, utilized in the credit policy development process at account acquisitions and account management.
    • Gathers and analyzes portfolio and macro-economic data to determine potential impact on business performance, and integrate the trends to the portfolio loss forecasts.
    • Conduct independent validation and monitoring of portfolio and vintage level loan performance compared to projections. Establishes baselines for strategies and tracks actual performance to expectations.
    • Applies predictive models, third party data and other tools to develop and execute appropriate segmentation and targeting for acquisition and portfolio strategies to provide insight/loss estimates into portfolio risk.
    • Collaborates with the line of business, Finance and Risk partners to assess and enhance operations processes related to Loss Forecasting activities for CCAR/DFAST and CECL.
    • Establish requirements for data maintenance and management and working with Technology on implementation. Create Management Loss Forecast reporting using Tableau or other cutting-edge visual interface-based tools to monitor portfolio performance at portfolio segment (e.g., product, vintage, risk segment, score band, or marketing channel), vintage and account levels to identify positive and negative trends such as improved portfolio quality or heightened delinquencies and recommend strategy changes to the Business.
    • Adhere strictly to compliance and operational risk controls in accordance with company and regulatory standards, policies and practices; report control weaknesses, compliance breaches and operational loss events. Address internal audit requirements and findings in a timely and appropriate manner (all encompassing)

    Basic Qualifications

    • 5 years of financial modeling, loss forecasting and business analytics related experience
    • 7+ years of experience working in risk management, data science, predictive modeling, loss forecasting or other similar quantitative functions across Consulting, Financial Services including Banks, FinTech, managing a consumer lending business
    • Strong Quantitative/ analytical skill with Master’s degree (U.S. or equivalent) in a quantitative discipline such as Mathematics, Statistics, Engineering, Data Science/Analytics or a related field like Information Systems, Business Analytics.
    • Experience in Loss Forecast process for unsecured consumer lending (e.g., installment loans, credit cards) preferred
    • Experience in retail credit risk analytics of retail strategy with  credit policy/underwriting criteria development, performing portfolio deep dive analytics including performance measurement and insight generation to influence credit policy (preferred)
    • Experience with statistical techniques including segmentation, decision trees and other advanced risk predictive modeling methods
    • Experience working cross functionally in a matrixed environment.
    • Strong Excel skills and experience using statistical tools such as SAS, SQL, R, Python (or similar) and big data platforms like Hadoop, Spark (or similar)
    • Strong interpersonal and presentation skills with the ability delivering key insights to management and non-technical personnel
    • Strong writing, presentation and communication skills with ability to deliver executive communication; technical writing and model documentation experience desired
    • Strong project management / organizational skills and the ability to manage multiple assignments concurrently




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