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Community Engagement Manager - Remote

Posted 2 days ago
All others
Full Time
Vietnam, Philippines

Overview

The Community Engagement Manager is responsible for promoting engagement strategies and ensuring community satisfaction while working with cross-functional teams in a multinational virtual environment.

In Short

  • Promote engagement strategies and monitor communication with community members.
  • Liaise with Technology Development, Delivery, and Marketing departments.
  • Set and manage community member expectations.
  • Conduct root cause analysis for community escalations.
  • Prepare presentations regarding community insights.
  • Implement strategies to maintain an engaged community.
  • Participate in onboarding processes for newcomers.
  • Track relevant community KPIs.
  • Organize community satisfaction surveys.
  • Review communication KPIs and workflows.

Requirements

  • Exceptional communication skills.
  • High-level interpersonal and relationship building skills.
  • Ability to work under pressure and meet deadlines.
  • Demonstrated analytical and problem-solving skills.
  • Coordination and resource planning abilities.
  • Experience with online platform development.
  • Ability to work independently.
  • Proactive in identifying risks and solutions.
  • Competency in business applications and collaboration tools.
  • Bachelor’s Degree or equivalent.

Benefits

  • Opportunity for professional growth in a global company.
  • Work in a multicultural environment.
  • Engage with a diverse community of contributors.
  • Possibility of contract extension after two years.
  • Flexible remote working arrangements.
TransPerfect logo

TransPerfect

TransPerfect is the world’s largest provider of language and technology solutions for global business, with a presence in over 100 cities worldwide. The company offers high-quality data for Human-Machine Interaction, catering to some of the most prestigious technology companies. Their DataForce division specializes in gathering, enriching, and processing data for Machine Learning across various AI domains, ensuring the development of advanced machine learning systems such as neural networks and generative models.

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