Data Analyst V (6347)

itD Tech•Phoenix, AZ

1d•Remote

About The Position

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 role involves working with large, complex datasets and combining customer signals from surveys, digital analytics, behavioral data, operational metrics, and support interactions. The analyst will use statistical methods, predictive analytics, machine learning, natural language processing, and Generative AI to inform customer-centric decisions and business improvements. This is a 12-month engagement with potential for extension or conversion. The schedule is 40 hours per week, Monday through Friday, with no overtime. The role is remote within the US, and candidates must be able to work Central or Pacific Time hours. Candidates must be direct W2 workers; sponsorship is unavailable. In addition to client work, the analyst will participate in itD practice activities, contribute to thought leadership and Digital Transformation materials, complete case studies and learning materials, attend networking events, and work with leadership on career development opportunities.

Requirements

Bachelor's degree in Analytics, Statistics, Mathematics, Computer Science, Data Science, Engineering, or a related field.
At least 8 years of experience in data analytics, data science, or a related field.
At least 2 years of experience in customer experience, customer support, customer insights analytics, or marketing analytics.
Strong SQL programming skills and proficiency in Python or R.
Proficiency in statistical analysis techniques, including correlation analysis, multivariate regression, and feature-importance methods.
Experience with predictive analytics, machine learning, or AI techniques.
Working knowledge of AI-powered analytical tools and Generative AI technologies, including LLMs and AI agents.
Ability to translate complex data from multiple sources into clear, actionable insights tailored to stakeholder needs.
Ability to collaborate with cross-functional teams and communicate technical findings to non-technical audiences.
Must be able to work Central or Pacific Time hours.
Must be a direct W2 candidate; sponsorship is not available.

Nice To Haves

Master's or Ph.D. degree in a quantitative field.
Experience with Customer Experience or Voice of Customer metrics, including NPS, CSAT, customer surveys, and customer feedback.
Familiarity with consumer electronics or retail businesses.
Experience with machine learning libraries and frameworks such as Pandas, scikit-learn, TensorFlow, or PyTorch.
Previous experience at Meta or another large technology company.

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 to analyze customer support conversations, transcripts, and tickets and 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.
Use Generative AI tools, large language models, and AI agents to automate data analysis, clean datasets, generate visualizations, and streamline analytical workflows.
Quantify the business impact and ROI of customer experience initiatives by connecting customer metrics with business outcomes.
Communicate analytical findings through clear reports and presentations, influencing stakeholders and driving corrective actions.
Attend regular internal practice community meetings.
Collaborate with the itD practice team on industry thought leadership.
Complete client case studies and learning materials, including blogs and media materials.
Build materials to contribute to the Digital Transformation practice.
Attend internal itD networking events, both in person and virtually.
Work with leadership on career fast-track opportunities.