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3 дня назад

Change Management Analyst (AI)

Тип работы
fulltime
Английский
b2
Страна
Portugal
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Change Management Analyst (AI): Overseeing the change management lifecycle in Portugal with an accent on AI-driven monitoring, predictive risk analysis, and data-informed decision-making. Focus on assessing change impact and rollback plans, preventing change-related incidents, optimizing resources, and building automated performance reporting and process improvements.

Location: Portugal, Porto

Company

hirify.global operates in financial markets and is hiring for its IT Operations and Service Management function.

What you will do

  • Support changes throughout their lifecycle and use AI tools to monitor progress and predict potential risks.
  • Prepare Change Advisory Board materials covering impact assessments, implementation plans, testing, and rollback plans.
  • Identify high-risk changes and help prevent change-related incidents through predictive analytics and AI-powered trend analysis.
  • Document post-implementation reviews, analyze feedback, and identify patterns for continuous improvement.
  • Use AI-based prioritization and resource allocation tools to align resources with high-value opportunities.
  • Report on change management performance and quality through AI dashboards and automated reporting.

Requirements

  • Experience or capability in change management processes across the full change lifecycle.
  • Ability to assess change impact, implementation, testing, and rollback plans for Change Advisory Boards.
  • Knowledge of incident and problem management process improvement.
  • Ability to develop metrics, maintain process documentation, and analyze operational data.
  • Ability to apply AI-driven analytics, process mapping, and optimization tools.
  • Work location: Portugal, Porto.

Culture & Benefits

  • Permanent employee position.
  • Focus on continuous improvement of efficiency, quality, and adoption.
  • Use of AI dashboards, automated reporting, and data-driven operational insights.

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