Home Credit US LLC

  • Senior Risk Analyst - Modeling

    Job Locations US-KS-Overland Park
    Posted Date 2 months ago(7/8/2019 4:09 PM)
    Job ID
    # of Openings
  • Overview

    What we’re all about


    At Home Credit US, our vision is to bring daringly different solutions to the connected world of consumer financing. In a world run by stuffy, institutionalized financial firms, we fiercely challenge the way things have always been done. Sounds fun, right?!


    What we’re looking for


    The Senior Risk Analyst with focus on modeling and reports to the Director of Risk Analytics.  This position is responsible for analyzing new and existing customer data to get deep insights into how to segment populations and how to assess the risk inherited in those segments. One of the primary tasks that come with this position is developing application and behavioral scorecards including rigorous analysis of data from credit bureaus as well as big data elements located in the Big Data Lake. The position also includes tasks such as comparing different workflows to identify ideal processes in scorecard development and offer creation, manage predictive models development, SQL data mining, applying machine learning algorithms to solve business problems, extracting raw data from credit bureau flat files and apply feature engineering to them as well as performing ad-hoc analyses. This individual will also propose and implement monitoring and reporting protocols to ensure accuracy of the scorecards and have proper back-testing mechanisms in place. The Senior Risk Analyst - Modeling will also visualize data insights and communicate them effectively to management. Creating reporting for regulatory purposes will be an additional responsibility of this role.


    If you are experienced analyst with a degree in Statistics, Mathematics, Business Analytics, Quantitative Analysis or a similar technical discipline, one of our Senior Risk Analyst roles may be for you.  The successful candidate will possess strong analytical, critical thinking/problem solving, detail-orientation, and verbal and written communications skills.  The ability to work effectively with colleagues across all business units will allow this individual to be most effective.


    A day in the life…

    • Develops or assist in developing of robust and compliant models predicting credit risk default, churn, fraud, collections effectiveness as well as profitability and other key indicators utilizing:
      • Traditional credit bureau data,
      • Application data
      • Customer behavioral data
      • Big data elements
      • And other permissible data sources
    • Develops application and behavioral scorecards
    • Proposes changes and process modification implementation
    • Proposes changes in scorecard development and offer settings to increase profitability
    • Applying machine learning algorithms to solve business problems
    • Extracting raw data from credit bureau flat files and apply feature engineering to them
    • Tests new approaches by combining external data sources with internal data
    • Maintains up-to-date models documentation
    • Prepares IT systems description documentation; modifying checks and process scripts; and prepares IT testing scenarios and manuals for employee use
    • Assists with developing machine learning algorithms 
    • Analyzes credit bureau data
    • Prepares visualizations of scorecard front- and back-end reports
    • Monitors scorecard performance indicators independently, proposing improvements to scorecards
    • Communicates with other departments and participate in knowledge sharing
    • Performs other duties as assigned


    You’ll own this if you have…

    • Master’s Degree in Statistics, Mathematics, Computer Science, Data Science/Analytics or related field
    • Minimum of 5 years of relevant experience in modeling and credit risk related fields
    • Deep understanding of common machine learning algorithms
    • Knowledge of risk techniques, systems, and strategies
    • Logical, Analytical and out-of-the-box thinking
    • Extensive experience with Python, R, SQL,
    • Experience with Tableau, and at least one object oriented programming language
    • Experience with data scraping and at least one scripting language
    • Proven ability to operate in a team environment and work in a matrix organizational environment
    • Strong analytical and problem-solving skills
    • Extensive feature engineering knowledge
    • Proficiency in Microsoft Office Suite (Word, Excel, Power Point) and VBA
    • Familiarity with visualization tools
    • Ability to work cross-functionally among numerous stakeholders
    • Excellent time management and written communication skills

    We would really like you to have...

    • PhD degree in Statistics, Mathematics, Computer Science, Finance, Economics or related field
    • Extensive experience in consumer risk management, credit risk, banking or credit bureaus
    • 10 years of modeling experience
    • Some international business exposure/experience
    • R, SAS or FICO Model Builder knowledge
    • Extensive programming experience in several functional and object oriented programming languages
    • Experience with deep learning and natural language processing algorithms and problems
    • Experience developing Tableau dashboards
    • Experience with process management tools

    We’ve got you covered…

    • Full benefits package, including health, dental and vision insurance
    • Competitive salary, based on experience
    • 401k, generous paid time off policy and a fully-paid holiday calendar.
    • We’re a certified Six Sigma organization, with all of our employees achieving white belt status or higher.
    • Flexible, “Dress for the Day” policy
    • Onsite and offsite activities, like ping pong tournaments, nerf gun wars and Nintendo brain-breaks
    • Volunteering and community engagement opportunities
    • All the coffee you can drink


    The technical stuff…

    Home Credit US is an Equal Opportunity Employer that does not discriminate on the basis of actual or perceived race, creed, color, religion, alienage or national origin, ancestry, citizenship status, age, disability or handicap, sex, marital status, veteran status, sexual orientation, genetic information, arrest record, or any other characteristic protected by applicable federal, state or local laws. 



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