Customer Success Manager (JN -092019-4032)

Our client is a fin-tech startup looking to find a motivated self-starter to join their Customer Success team. The Customer Success Manager is responsible for the onboarding, delivery, and delight of their Strategic and Enterprise Customers. The company accomplish this with a constant customer focus, advocating for the client internally and working in partnership across all the teams to achieve the customer’s goals and provide solutions for the customer’s challenges.

Qualifications / Requirements

  • An excellent communicator, comfortable with delivering presentations and able to build authentic business relationships with senior customers.
  • Excellent project management, time management and organizational skills.
  • Able to interpret/analyze data, draw conclusions and construct a clear narrative.
  • A commercially minded individual with strong business acumen.
  • A storyteller who can influence and persuade.
  • Passionate about client success and buyer satisfaction.
  • A logical and analytical mind who enjoys working with CRM systems, MS Excel, data and reporting tools.
  • Fluent in English.

Responsibilities

  • Leading all post-onboarding activity through strong relationship-building, product training, program planning, and execution.
  • Proactively partnering with customers on an on-going basis to drive optimal results – understanding and explaining performance data, delivering product training, and developing change management programs to drive product adoption.
  • Regularly monitoring learning KPIs and reporting to clients on success of learning programs to drive results, achieving renewals and assisting Sales in growing the accounts.
  • Foreseeing and reacting to problems rapidly with creative solutions.

Education / Training

  • University graduate, preferably with a Business degree. Master Diploma is a plus.

Background

  • 2+ years of customer-facing experience in customer success, account management, consulting or sales.
  • Proficiency with SQL, R, Python, or other statistical programming languages