Collections Data Analytics Specialist - North American Region

Volkswagen Financial Services, a wholly-owned subsidiary of Volkswagen Group, is the trusted key to mobility for its brand partners. We are committed to supporting the Audi, Ducati, and Volkswagen brands and their Dealers, specializing in providing accessible mobility solutions for its Customers. The company’s offerings include Retail Leasing, Retail Financing, Commercial Financing for new and used vehicles, and End-of-Term vehicle disposition.

Role Summary:

The Data Analytics Specialist – Collections utilizes analytical and statistical methods to identify opportunities to continuously drive improvements in collections effectiveness. The Specialist is responsible for reporting on the effectiveness of collections strategies. And works within VWFS’s risk management framework to identify and pursue opportunities that enhance the collectability of impaired assets by improving the decision tools, treatments and contact strategies used within the collections processes. The Specialist will also have experience in strategy analytics, meaning drawing business insights from data and applying critical thinking in support of business goals.

Role Responsibilities:

Main responsibility – Operational 60 % of time spent

· Support Collections Department strategy, analytics, and reporting for early-stage collections. Early-stage collections includes X-59+ collections support, specifically vendor activity (collections accounts placed with vendors), In-House predictive dialer and early stage manual collections.

· Assist Strategy Manager with the development and deployment of performance monitoring dashboards and skills assessment reporting in collaboration with other members of Service Center Operations.

· Monitor and report on late-stage collections and process. Including post charge off recoveries.

· Monitor and report on fraud performance (committed and recovered), working closely with the Fraud team.

· 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.

· Utilize analytic tools (i.e. SAS, SQL, Tableau, Python, R) data query tools to build, test, evaluate, and maintain robust data analysis and reporting for collections teams to make timely, informed decisions.

· Develop A/B tests and pilots and oversee the overall quantitative testing strategy for collections.

· Analyze data and create and validate assumptions that feed into volume, growth, headcount and profitability strategies.

· Drive analytics to enhance understanding of collections data across VWFS

· Risk scorecard understanding and analysis including; cut-off analysis, score-based portfolio segmentation, profitability analysis and the monitoring of scorecards

Additional responsibilities – Strategic 40% of time

· Collaborate with members of Risk Management and Service Center Operations to identify areas where quantitative analysis and modeling is required to improve business performance

· Educate colleagues on proper statistical principles and methodology; sell ideas and conclusions in a clear, concise manner to colleagues with limited statistical background

· Collaborate across Consumer Risk group to ensure initiatives are aligned with the established risk appetite

· Identify areas of opportunity where data science can improve business results or increase process efficiency; demonstrate effective planning, research and implementation of statistical models

· Effectively communicate risk performance and strategies throughout the business at all levels.

Provide portfolio performance based reports that support the lease and loan asset backed securities transactions as directed by the Treasury department.

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 VWFS 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%

Role may require occasional/seasonal work outside of normal working hours.

Volkswagen Financial Services is committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, family status, gender identity, gender expression, national origin, age, disability or any other characteristic protected by federal, or local laws. Volkswagen Financial Services is committed to accommodating applicants and employees with disabilities. Should you require an accommodation during the recruitment and selection process please advise in advance.