Especialista de Performance CX

New
J
JobgetherCustomer experience
Work from anywhere within Brazil, with the option to visit or work from the São Paulo office.Full-Time
Salary not disclosed
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Job Details

Required Skills
SQLMicrosoft ExcelGoogle SheetsPrompt Engineering

Requirements

  • Experience in operational performance, applied analytics, customer experience (CX), Customer Success, or operational intelligence in a senior or specialist-level role.
  • Ability to improve customer experience metrics through data analysis and practical use of technology and AI in daily operations.
  • Advanced hands-on experience with LLMs such as ChatGPT, Claude, or Gemini for data analysis, text summarization, sentiment analysis, contact-reason classification, prompt engineering, or prototyping AI-powered insights and agents.
  • Ability to independently query, combine, and analyze large datasets using advanced SQL.
  • Advanced Excel and Google Sheets skills, including data modeling, scenario simulations, tactical reporting, and spreadsheet-based automation.
  • Experience with Google Apps Script for spreadsheet-based automation.
  • Familiarity with root cause analysis methods such as the 5 Whys, Ishikawa diagrams, MECE, and Pareto analysis.
  • Ability to translate technical analyses, data findings, and AI-generated recommendations into actionable processes for CX leaders and frontline teams.
  • Preferred: experience building workflow automations or AI agents with Make, n8n, LangChain, the OpenAI API, or Python.
  • Preferred: experience in B2B customer experience or Customer Success operations.

Responsibilities

  • Monitor daily and weekly B2B CX indicators, including demand, AHT, repeat contacts, FCR, and SLAs.
  • Run performance reviews, weekly check-ins, and response sessions for critical deviations.
  • Develop and implement action plans with frontline teams to address performance gaps.
  • Analyze quantitative data and qualitative sources such as call transcripts, chat logs, customer feedback, and contact reasons to identify root causes.
  • Use LLMs and AI assistants to summarize feedback, analyze unstructured data, and generate hypotheses.
  • Identify and develop lightweight AI agents and analytical automations, including repeat-contact categorization and ticket summarization.
  • Partner with Process and Training teams to improve workflows, routing strategies, agent AI assistants, and service scripts.
  • Coordinate with Workforce Management and Planning teams on staffing, scheduling, and capacity forecasts.
  • Translate analytical findings and AI-generated insights into operational recommendations for B2B CX leadership.
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