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Manager – Loss Prevention Strategy and Analytics

Location: Wilmington, DE (Hybrid)  

We are looking for a Manager to join our Loss Prevention Strategy and Analytics team in Wilmington, DE.  This is an exciting opportunity to deepen consumer credit analytics skills and develop strategies to help past due customers get back on track. 

Through credit analytics and a hypothesis-driven test and learn focus, this individual will help drive material improvements to the economics and customer outcomes within the Loss prevention team, with a particular focus on credit performance monitoring and modeling, contact strategy optimization, and development and advancement of the tools designed to support past due customers. 

The Role

• Working within cross-functional teams, they will create important insights into the effectiveness of our current strategies, identify key opportunities for improvement and develop business cases and testing plan to execute against those opportunities. 
• This individual will expand their competencies and grow their business and industry acumen, as well as demonstrate the ability to work on complex processes or projects across the end-to-end project cycle.
• Design, recommend, document, and execute loss prevention strategies via extracting and analyzing requisite historical customer performance data from multiple disparate systems.
• Utilize data query tools (i.e., SQL, Python, R, etc…) and decision tree analytical software to develop, test and execute new strategies and segmentation schemes.
• Leverage traditional regression model and machine learning algorithms to understand the key drivers and estimate customer behaviors by different strategy treatment.
• Implement Quality Control processes to ensure data accuracy. 
• Continually enhance existing processes and reporting through automation, quality control, presentation and insights.
• Effectively summarize and present results and insights to management.

Requirements

• Bachelor Degree (Graduate Preferred) in a quantitative discipline such as Engineering, Statistics, Economics, or Computer Science and 3+ years of relevant analytical experience.
• Strong SQL, Python and Excel skills required; experience with multiple types of relational databases, BI tools/platforms, and/or additional programming languages is a plus.
• 4+ years of experience in a complex, data-driven problem solving environment
• Innovative and capable of developing a highly analytical approach to solving problems
• Lending or consumer finance industry experience preferred

Who We Are

OneMain Financial (NYSE: OMF) is the leader in offering nonprime customers responsible access to credit and is dedicated to improving the financial well-being of hardworking Americans. Since 1912, we’ve looked beyond credit scores to help people get the money they need today and reach their goals for tomorrow. Our growing suite of personal loans, credit cards and other products help people borrow better and work toward a brighter future.

Driven collaborators and innovators, our team thrives on transformative digital thinking, customer-first energy and flexible work arrangements that grow lives, careers and our company. At every level, we’re committed to an inclusive culture, career development and impacting the communities where we live and work. Getting people to a better place has made us a better company for over a century. There’s never been a better time to shine with OneMain.

Because team members at their best means OneMain at our best, we provide opportunities and benefits that make their health and careers a priority. That’s why we’ve packed our comprehensive benefits package for full- and some part-timers with:

• Health and wellbeing options including medical, prescription, dental, vision, hearing, accident, hospital indemnity, and life insurances 
• Up to 4% matching 401(k)   
• Employee Stock Purchase Plan (10% share discount)   
• Tuition reimbursement   
• Paid time off (15 days’ vacation per year, plus 2 personal days, prorated based on start date) 
• Paid sick leave as determined by state or local ordinance, prorated based on start date 
• Paid holidays (7 days per year, based on start date)