Octane

Octane

Collections Portfolio Specialist

Irving, Texas, United States

Sponsorship not specifiedDetected 10 days ago
SalesNegotiationOutbound SalesCustomer SupportCommunication

About the role

  • Octane is unlocking the power of financial products for merchants and consumers.
  • Octane is hiring Collectors to join Roadrunner's Operations Center in Irving, Texas.
  • Successful candidates will be honest, with a strong work ethic, few unscheduled absences, and always punctual.

Responsibilities

  • Maintain delinquency and mitigate losses by conducting outbound and Inbound collection and customer service calls.
  • Our cutting-edge technology and innovative financial products empower businesses with more control and flexibility, enabling them to deliver seamless digital experiences, drive customer loyalty, and build long-term value.

Requirements

  • Working knowledge of Word and Excel.
  • They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified.
  • All personnel may be required to perform duties outside of their normal responsibilities from time to time, as needed.

Nice to have

  • HS Diploma or GED required (some college coursework a plus) followed by preferably two years of collections and or servicing experience, ideally in auto finance or an installment loan portfolio.
  • Lease servicing experience a plus.
  • Bilingual English/Spanish a plus.
  • Basic understanding of finance/lending
  • Possess excellent written and verbal communications skills

Benefits

  • Robust Health Care Plans (Medical, Dental & Vision)
  • Up to 20 Days PTO (Accrued)
  • Generous Parental Leave
  • Retirement Plan (401k with Company Match).
  • Educational Assistance/Tuition Reimbursement up to $3K/year
  • Recreational Safety Benefit
  • Wellhub (Gympass) Wellness Benefit

Company info

  • Advance win-win solutions to assist customers with payment extensions and refinance options.

This listing is sourced directly from Octane's careers page and normalized into a canonical job model.