Sr. Data Scientist

at  Exeter Finance LLC

At Exeter Finance, we are committed to helping customers find the right financing for their next vehicle purchase. By building strong relationships with our customers and network of dealer partners we are able to give options that make sense, getting customers behind the wheel of their car.
Every team member is integral to our success. Whether you’re at a servicing center helping customers with their loans, in the field building relationships with dealers, or supporting the company from its corporate offices, you’ll enjoy a nurturing, invigorating and positive work environment.
Our vision is to be a premier finance company and lender of choice known for its People, Performance and Service.
Job Description
Job Summary:
The Data Scientist will play a vital role in the development and implementation of predictive models for a non-prime auto lender. This position will make valuable contributions to every step in the model life-cycle including but not limited to: Model Development, Model Implementation, and research into Statistical Modeling Techniques.

Job Duties:

• Use robust and powerful machine learning algorithms to develop predictive models that can be deployed to improve profitability across the entire life-cycle of an auto loan.
• Keep abreast of new developments in the industry, conduct research into new algorithms and mathematical techniques, develop and test working prototypes and make tangible improvements to existing modeling processes
• Create datasets for development of predictive models.
• Communicate effectively with business users about various aspects of model development, model results and theoretical underpinnings of various modeling techniques.
• Work with IT to ensure models are implemented correctly.
• Perform ad hoc analyses related to model performance.
• Other duties as assigned.

Education and Work Experience:

• Bachelor’s or higher degree in Data Science, Statistics, Mathematics, Business Analytics or other analytical discipline
• Two (2) plus years of statistical programming experience in R. Applicants may be tested for their skill level in R programming. Python is a plus.
• Two (2) plus years of experience using SQL Server or other relational databases to extract data for model development and analysis. Experience with Microsoft SQL Server strongly preferred
• One (1) plus years of experience developing predictive models. Prior experience working with logistic regression models strongly preferred and familiarity with machine learning algorithms like Random Forests and Generalized boosted regression models preferred.
• Retail finance industry especially Auto Finance strongly preferred.
• Experience working with credit bureau data preferred
• An interest in problem solving and the ability to multi-task on different projects of varied nature
• Excellent written and oral communication skills with good interpersonal skills
• Demonstrable knowledge of statistical concepts and methods, and practical experience applying advanced analytical methodologies
• Ability to deal with a large amount of both structured and unstructured data; fluency with SQL or SQL-like tools
• Ability to communicate complex models and analysis in a precise and clear manner

Exeter Finance LLC is an Equal Opportunity Employer.
Individual compensation packages are based on various factors unique to each candidate including
skill set, experience, qualifications and other job-related reasons.

• Use robust and powerful machine learning algorithms to develop predictive models that can be deployed to improve profitability across the entire life-cycle of an auto loan.
• Keep abreast of new developments in the industry, conduct research into new algorithms and mathematical techniques, develop and test working prototypes and make tangible improvements to existing modeling processes
• Create datasets for development of predictive models.
• Communicate effectively with business users about various aspects of model development, model results and theoretical underpinnings of various modeling techniques.
• Work with IT to ensure models are implemented correctly.
• Perform ad hoc analyses related to model performance.
• Other duties as assigned