Location: Overland Park, KS

Job description

• The Senior Risk Analyst with focus on modeling reports to the Head of Analytics. This position will be 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 will be developing application and behavioral scorecards including rigorous analysis of data from credit bureaus as well as big data elements located in the Sprint 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 and also 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 will also visualize data insights and communicate them effectively to management. Creating reporting for regulatory purposes will be an additional responsibility of this role.
• The focus of this position is developing robust and compliant predictive models that focus on credit risk default, churn, fraud detection, collection strategy as well as profitability.
• If you are a seasoned analyst with a degree in Business, Statistics, Mathematics, Quantitative Analysis or a 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 robust and compliant predictive models utilizing big data elements from the telecommunications industry
• Develops robust and compliant predictive models including but not limited to credit risk default, churn, fraud detection, collection strategy as well as profitability
• Develops application and behavioral scorecards Proposes changes and process modification implementation Proposing 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 scorecard and profitability model 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 will own this if you have Masters Degree in Statistics, Mathematics, Computer Science 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 and out-of-the-box thinking
• Experience with deep learning and natural language processing algorithms and problems
• Experience with Python, R, SQL, 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

PREFERRED QUALIFICATIONS

• 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 SAS and FICO Model Builder knowledge
• Extensive programming experience in several functional and object oriented programming languages
• Experience developing Tableau dashboards.Experience with process management tools