Data Analyst
Posted 14 Oct 2026
Advertised as “Data Analyst V (6347)”
BranchFactor Summary
The original posting with the fluff stripped out
- Level
- V
- Expected experience
- 8+ yrs
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Contract
- Visa sponsorship
- Not offered
No salary listed for this role.
Field of studyAnalytics, Computer Science, Data Science, Engineering, Mathematics, Statistics (or related)
Study levelBachelor's
Study levelMaster's or higher
Data Analyst V
itD is seeking a Data Analyst V to analyze customer experience and customer support data for Reality Labs, uncover actionable insights, and improve customer satisfaction across the end-to-end customer journey. The ideal candidate will bring 8+ years of experience in data analytics or data science, strong SQL and Python or R programming skills, and expertise in statistical modeling, predictive analytics, and Generative AI to translate complex customer data into insights that drive business improvements and customer-centric decisions.
Location: Remote – US (Candidates must be able to work Central or Pacific Time hours)
Duration: 12 months, with potential for extension or conversion
Schedule: 40 hours per week, Monday–Friday; no overtime.
We provide comprehensive medical benefits, a 401k plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship.
Responsibilities
- Analyze large, complex datasets using SQL, Python or R, and statistical techniques to identify customer experience trends, pain points, and opportunities for improvement.
- Synthesize customer signals from surveys, digital analytics, behavioral data, operational metrics, and customer support interactions across the end-to-end customer journey.
- Apply statistical modeling, predictive analytics, machine learning, and natural language processing (NLP) to analyze customer support conversations, transcripts, and tickets to generate actionable insights.
- Develop customer segmentation and clustering models to identify common customer issues and recommend targeted solutions, including self-service resources.
- Integrate customer feedback with transactional, operational, and behavioral data to identify key drivers of customer satisfaction and business outcomes.
- Design, test, and launch customer experience and support metric scorecards to track KPIs and evaluate performance across digital, AI-powered, and human-assisted support channels.
- Leverage Generative AI tools, large language models (LLMs), and AI agents to automate data analysis, clean datasets, generate visualizations, and streamline multi-step analytical workflows.
- Quantify the business impact and ROI of customer experience initiatives by connecting customer metrics with business outcomes.
- Communicate complex analytical findings through clear, compelling reports and presentations, influencing stakeholders and driving corrective actions.