CX Data Scientist

Required Skills & Experience
• \t6+ years of experience in data analytics, data science, or related analytical roles.\n• \t6+ years of work experience in analytics, data querying languages such as SQL, and statistical analysis methods\n• \tExperience with data-led storytelling and demonstrated experience in conveying complex insights to non-technical stakeholders\n• \tExperience working with Customer Experience or Voice of Customer metrics (NPS, CSAT, etc.), surveys, and customer feedback\n• \tExperience working with customer support operational metrics \n• \tExperience with statistical analysis techniques and utilizing R, Python, or similar scripting languages/tools.

Nice to Have Skills & Experience
• \tMaster's degree in Computer Science, Data Science, Statistics, Mathematics, or related field\n• \t3+ years of experience in customer experience, customer support, customer care, or other service-related analytics roles\n• \tProficiency in AI-powered tools: Demonstrated working knowledge of Generative AI technologies (e.g., LLMs and AI agents), with experience designing, prompting, and orchestrating AI systems (e.g., prompt engineering) to automate data analysis, synthesize insights, and execute multi-step analytical tasks (e.g., prompting agents to clean datasets or build visualizations).\n• \tExperience working with Salesforce \n• \tKnowledge of predictive analytics or ML/AI techniques

Job Description

As a CX Analyst for Reality Labs’ Customer Experience (CX) team, you will join a global team leveraging customer feedback to drive service improvements and business growth. You will analyze support surveys and operational data to identify improvement areas and partner with cross-functional teams to implement enhancement strategies. By applying your expertise in data analysis and storytelling, you will help define the future of our customer support program.\n\nResponsibilities \n• \tIdentify trends, opportunities, and pain points across Reality Labs' customer support channels using various data sources (customer support operational data, case transcripts, surveys, and other relevant data).\n• \tMonitor customer feedback to identify emerging trends and issues and perform root cause analysis.\n• \tIntegrate customer feedback data with other transactional, operational, and behavioral data sources to create a comprehensive picture of experience drivers.\n• \tAdvocate for customers and influence corrective actions through periodic and ad-hoc reporting, proactively evangelizing insights among key stakeholders.\n• \tCollaborate with cross-functional teams to identify root causes of customer issues within support functions and develop action plans to remediate and measure effectiveness.\n• \tUtilize various systems and tools (AI analytics tools, Salesforce, Hive) to analyze and deliver insights.\n• \tPresent insights and recommendations to stakeholders and executives through compelling and engaging presentations.