Originations Data Analytics Specialist - NAR
Employment Type : Full-Time
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The Originations Data Analytics Specialist – North American Region (NAR) utilizes analytical and statistical methods to quantify credit risk, automate and optimize lending decisions, and forecast credit performance. The Specialist is responsible for reporting on the effectiveness of credit risk management strategies directly related to originations. And works within the VCI risk management framework to identify, measure, mitigate, monitor and report on credit risk. Supports Consumer Risk’s efforts to provide strategic guidance to steer management towards data-driven business decisions that impact credit originations strategy, pricing, planning round and budget setting.
Role Responsibilities:
- Monitor VCI & VCCI’s Company’s consumer portfolios for change in behaviors on a monthly basis, using static pool, trend, regression and time series analysis, correlating demonstrated changes in repayment behaviors of customers utilizing a robust segmentation analysis. Identify specific areas or markets of trade that represent above average potential for loss, repossession or prepayment. (25%
- Support the Originations Strategy Manager with the design, development, testing and execution of the models used in the Originations strategy for the consumer credit portfolio (25% of the time)
- Leveraging data and various data analytic tools (i.e. SAS, SQL, Tableau, Python, R,), to determine and explain changes in borrowers’ credit quality originated into the portfolio.
- Automation of credit underwriting monitoring. Including lowside and highside, quality overrides and other policy exceptions. Draw conclusions and make recommendations to the Director of Credit Risk for developing or modifying existing credit policies.
- Support in the preparation and presentation of a comprehensive quarterly Credit Committee package. Using rigorous analysis and monitoring to connect drivers of future consumer credit trends to historical behavior, provide recommendations and solutions to business leaders in response to the identification of new and existing risks and drive remediation when control metrics are outside of targets.
- Support the Strategy Mangers efforts to test strategies to increase the rate of automated decisioning. Ensure changes to processes are documented and monitored to prevent unforeseen changes in the level of fraudulent activity or increase risks in portfolio performance.
- Analyze and evaluate potential vendors/data providers for incremental value in credit management strategies in a continuous improvement environment.
- Support the development of portfolio performance statistics used in all capital markets transactions executed by VCI in support of funding the growth in the consumer portfolio. Performance statistics developed will be a key component in determining credit enhancement levels by Rating Agencies and Due Diligence for Asset Backed Securitzation (ABS) transactions. Prepare delinquency and loss reporting for prospectus materials as well as presentations required by investors during ABS roadshows and on-site visits.
- Represent the Risk Management consumer credit team in the Data Stewards and Resource Sub-committee. Work with the data stewards to develop data quality validation processes and partner with cross-functional users of the data warehouse to identify operational and reporting data quality issues. As needed, work with IT and the business in identifying solutions and testing data fixes (10%)
- Support ad hoc requests in areas related to related to consumer portfolio performance (10%)
Experience:
- 5-7 years of professional experience
- 3+ years in utilizing methods and tools to extract, curate, explore, and analyze data from large data sources
- 3+ years in developing decision science algorithms
- 2+ years in the fundamentals of big data
- 1-2 years working in a Predictive Analytics or Statistical Modeling-related role
- At least one (1) year of banking or credit risk experience
Education:
Required –
- Bachelor’s Degree in a quantitative discipline: Statistics, Mathematics, Economics, Finance, Operations Research
Desired –
- Master’s degree in Statistics, Finance, Computer Science, Economics or Operations Research or similar quantitative STEM field
- Additional certifications in data sciences or analytics related fields
General Skills:
- Ability to conduct large scale projects and research through all stages: concept formulation, definition of metrics, determination of appropriate methodology, research evaluation and final research report
- Demonstrated understanding and experience with relational datasets, data warehouses, data mining and data analysis techniques
- Ability to effectively communicate technical subjects to business stakeholders and audience who have limited background in mathematics or statistics
- Analytical and conceptual thinking – ability to understand business problems and develop data-driven solutions
- Embrace, research, explore, and enable new quantitative techniques and technologies in credit risk that will help define VCI as an industry leader in this area
- Passion for data analytics and problem solving
Specialized Skills:
Required –
- Working knowledge of basic statistical analyses including regression analysis, time series forecasting and other multi-variate analyses
- Well versed in methods and tools to extract, curate, explore, and analyze data from large data sources (e.g. SQL, SAS, Python, R).
- Ability to work effectively across portfolio risk teams and functional areas teams
- Extensive experience in the fundamentals of data/analytics algorithms and data structures
- Advanced knowledge in model back-testing, validation, and ability to know when a model has degraded beyond the original expected outcomes
- Building, improving or analyzing risk management in consumer lending or similar data driven industries like insurance
- Experience gaining insights from U.S. credit bureau data, Risk Scorecards and ability to pay quantification methods
- Strong communication and presentation skills targeting a variety of audiences
- Proficiency with Microsoft Office applications
Desired –
- Advanced knowledge of applied statistical methodologies.
- Advanced knowledge of machine learning (ML) approaches to influence business decisions (SAS, Spark, Azure, TensorFlow)
Work Flexibility:
- Minimal travel – 5%
- Flexibility to work remotely on as-needed basis
- Role may require occasional/seasonal work outside of normal working hours
We are proud to be an EEO employer M/F/D/V. We maintain a drug-free workplace and perform pre-employment substance abuse testing.