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Product Manager - CS Internal Tools & Operations

9 months

In short

Seeking a Product Manager for Customer Service Internal Tools & Operations focusing on product lifecycle, multi-channel support, AI-driven improvements, and stakeholder collaboration. Requires 3-5 years PM experience and strong communication skills.

Where
Remote · Taiwan
Level
Mid-level · Full-time
Binance
Binance
5 open roles · usually open about 4 weeks

Responsibilities

  • Responsible for the end-to-end product lifecycle of Customer Service (CS) management systems, specifically focusing on Quality Assurance (QA), Performance Management, Learning & Training systems, and Notification Centers.
  • Maintain and enhance multi-channel service tools (Ticketing System, Email, Whistleblowing, Outbound), ensuring stability and operational efficiency for global CS teams.
  • Leverage AI and automation to upgrade traditional management workflows. Examples include AI-assisted QA scoring, automated performance reporting, and smart task distribution.
  • Partner closely with CS Management, QA, Training, and Compliance teams to identify operational bottlenecks and translate complex business requirements into scalable product solutions.
  • Monitor key usage metrics of internal tools (e.g., system adoption rate, processing time) and utilize data insights to drive continuous product optimization and reduce administrative overhead.

Requirements

  • Bachelor’s degree or above; 3-5 years of product management experience, preferably in CRM, SaaS, B2B internal tools, or Contact Center systems.
  • Familiarity with CS operations workflows (QA, Training, Performance) or ticketing systems (e.g., Zendesk, Salesforce) is a strong plus.
  • Strong ability to design complex workflows and permission systems. Capable of handling intricate logic behind backend management consoles.
  • Excellent communication skills to align with multiple internal stakeholders (Operations, Legal, Compliance, Dev) in a fast-paced global environment.
  • Proficiency in data analysis and a good understanding of how to apply LLM/AI to internal operational scenarios.
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