Ampcus Inc

Ampcus Inc

"Recoveries Analyst" or "Customer Service Representative"

Austin, TX, United States

Sponsorship not specifiedDetected 3906 days ago
ComplianceAccount ManagementExcelCustomer SupportCommunicationProblem SolvingWriting

About the role

  • Confidential* Hello, We have direct client requirement.
  • Thanks & Regards, Shalini Sajeev Ampcus Inc.
  • If you are not the intended recipient, please delete without copying.

Responsibilities

  • Suggest and implement new risk strategy recommendations for system and process enhancements to mitigate future losses
  • Collaborate with Customer Service and other teams within the Risk Department on special projects
  • Ability to gather facts and deliver unwanted news with diplomacy
  • 14900 Conference Center Drive

Requirements

  • Strong customer service background required
  • prefer experience with escalated calls

Skills

  • Strong customer service background required; prefer experience with escalated calls
  • One or more years of previous experience in collections or fraud analysis preferred
  • Ability to analyze financial transactions and investigate suspicious activity
  • Strong math skills and problem solving skills, with extreme attention to detail
  • Ability to multi-task and work on various accounts and issues consecutively
  • Prefer familiarity with the following:
  • ACH, NACHA, processing in payment card industry or bank back office
  • Proficient in MS Word, Excel and Access
  • Ability to work flexible schedule
  • Experience working for a bank, financial institution, or with billing statements preferred
  • Experience in database management, analysis and data mining preferred
  • College degree preferred, but not required

Benefits

  • Skills/Education/Experience:

Company info

  • Excellent writing skills with the ability to communicate effectively to customers, co-workers and management

Visa & Work Authorization

  • Process chargebacks with the card associations (MC/Visa)

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