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VP Data Science- GM Protections

AT GM Financial
GM Financial

VP Data Science- GM Protections

Fort Worth, TX

Overview

Why GM Financial?

GM Financial is the wholly owned captive finance subsidiary of General Motors and is headquartered in Fort Worth, U.S. We are a global provider of auto finance solutions, with operations in North America, South America and the Asia Pacific region. Through our long-standing relationships with auto dealers, we offer attractive retail financing and lease programs to meet the needs of each customer. We also offer commercial lending products to dealers to help them finance and grow their businesses.

At GM Financial, our team members define and shape our culture - an environment that welcomes new ideas, fosters integrity and creates a sense of community and belonging. Here we do more than work - we thrive.

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Our Purpose: We pioneer the innovations that move and connect people to what matters

GM Financial is targeting significant growth as it transforms the Protection/Insurance Products into a full captive platform. Our team is responsible for bringing the branded General Motors F&I products to market and we work hands on with our dealer partners to improve performance in their F&I department. In order to provide the most competitive products and business insights, we are building advanced data and analytics capabilities.

The VP of Data Science- GM Protections will be responsible for the success of data science and machine learning solutions for marketing and claims management. You will use your excellent communication skills to share your vision for data science with senior leaders to shape the future of GM Protections. You will be the technical lead responsible for breaking down large initiatives into achievable challenges with quantitative success criteria; to design, develop and deploy machine learning models, algorithms, and other data processing techniques.

Hybrid work environment - three days in office.

Responsibilities

About the role:

  • Researches, develops, and implements traditional and innovative algorithms through application of statistical, and machine learning methods
  • Employs advanced methods to query, calculate, transform, and manipulates data from databases using Databricks, SAS, SQL, Python, R, or similar. Performs reasonable methods to validate data integrity
  • Pursues problem identification and impact across large data sets, leveraging data mining, machine learning, simulation and visualization techniques to further enhance insight and internal performance optimization
  • Develops and builds analytical solutions based on ambiguous business needs/want's, models and delivery methods
  • Design and develop modeling packages for marketing and claims management that can be deployed in a compliant and scalable manner
  • Advise business and technology teams on data science elements on business roadmap
  • Partner with vendor(s) and internal departments to ensure tasks are defined and documented with timely deliverables and within SLA

Qualifications

What makes you an ideal candidate:

  • Experience with advanced statistical methods
  • Efficient modeling skills with very large datasets
  • Comprehensive knowledge and experience with technical systems, datasets, data warehouses, and data analysis technique
  • Experience in digital marketing and insurance operations preferred
  • Strong quantitative, analytical and data interpretation skills with a solid foundation of mathematics, probability and statistics.
  • Proficient in Databricks, SQL, Python, R, Spark, and other common data science software languages.
  • Strong knowledge of engineering practices that pertain to data science, such as version control, CI/CD, model deployment, and model monitoring.
  • Proficiency in experimental design and using behavioral design in tandem with data science.
  • Ability to be curious in all aspects of the business and continuously learn.
  • Ability to identify and understand business issues and map these issues into quantitative questions.
  • Exceptional communication skills for both technical and non-technical audiences.

Education

Master's Degree in Computer Science, Data Science, Applied Mathematics, Statistics or similar quantitative field required

Experience

8 or 9+ years experience in modeling required

4+ years experience in management and/or leadership required

What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), training, GM employee auto discount, community service pay and nine company holidays.

Our Culture: Our team members define and shape our culture. We have an environment that welcomes new ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work - we thrive.

Compensation: Competitive salary and bonus eligibility; this role is eligible for company vehicle program

Work Environment

Hybrid work environment - three days in office

Some travel may be required to support business needs

Normal office environment

#LI-WB1

Salary

The base salary range for this role is: USD $174,000.00 to $330,500.00. At GM Financial, we strive for transparency in all aspects of our business, including pay equity. This is the GM Financial pay range for this role and job level. The exact salary and compensation will vary based on factors like knowledge, skills, experience, and education. This role is eligible to participate in a performance-based incentive plan. Full time employees are eligible to participate in health benefits on day one of employment.

Client-provided location(s): Fort Worth, TX, USA
Job ID: GM_Financial-49261
Employment Type: Full Time

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • Short-Term Disability
    • Long-Term Disability
    • FSA
    • FSA With Employer Contribution
    • HSA
    • HSA With Employer Contribution
    • Mental Health Benefits
    • Fitness Subsidies
  • Parental Benefits

    • Birth Parent or Maternity Leave
    • Non-Birth Parent or Paternity Leave
    • Adoption Leave
  • Work Flexibility

    • Remote Work Opportunities
    • Hybrid Work Opportunities
  • Office Life and Perks

    • Happy Hours
    • Company Outings
    • On-Site Cafeteria
    • Holiday Events
  • Vacation and Time Off

    • Paid Vacation
    • Paid Holidays
    • Personal/Sick Days
    • Leave of Absence
    • Volunteer Time Off
  • Financial and Retirement

    • 401(K) With Company Matching
    • Performance Bonus
    • Profit Sharing
  • Professional Development

    • Tuition Reimbursement
    • Promote From Within
    • Mentor Program
    • Shadowing Opportunities
    • Access to Online Courses
    • Lunch and Learns
    • Internship Program
    • Leadership Training Program
  • Diversity and Inclusion

    • Unconscious Bias Training
    • Employee Resource Groups (ERG)