Statistical Analyst - Data Analystics

We are seeking an analytical and business-minded Statistical Analyst to join our Global Support Organization. This role focuses on transforming complex support data into actionable insights that improve customer experience, operational efficiency, and strategic decision-making.

The ideal candidate combines strong statistical rigor with hands-on experience in operational data and a passion for clear, compelling data visualization.

About the Team

The Support Analytics and Operations team consists of 6+ analysts covering various Nutanix products and core components.

The team reports to the Manager of Support Analytics and Operations.

Your Role

Technical Support & Operations Analytics

• Analyze technical support data to identify trends in case volume, backlog, resolution time, escalations, and customer experience.
• Segment and diagnose performance by factors such as issue type, priority, product, region, support tier, and ownership.
• Define, maintain, and evolve operational KPIs and performance metrics.
• Identify risks and opportunities related to workload, service levels, and customer outcomes.

Statistical Analysis & Modeling

• Apply statistical techniques including trend analysis, regression, hypothesis testing, segmentation, and forecasting.
• Perform root-cause analysis to identify key drivers of performance variability.
• Develop analytical models for backlog forecasting, service-level risk identification, and capacity planning.
• Evaluate the impact of process and policy changes using pre/post and controlled analyses.

Data Visualization & Analytical Storytelling

• Design and maintain interactive dashboards and reports using enterprise visualization tools.
• Create visualizations that emphasize trends, drivers, and leading indicators rather than static metrics.
• Translate complex analyses into clear, executive-ready narratives.
• Tailor insights and visualizations for different audiences, from operational leaders to executives.

Data Querying & Analytics Enablement

• Extract, transform, and analyze support data using SQL and analytics platforms.
• Partner with data engineering teams to support data models, transformations, and integrations.
• Understand data refresh cycles, latency, and lineage to ensure reliable and trusted reporting.

Business Partnership & Influence

• Partner with Support leadership to understand business questions and priorities.
• Proactively identify opportunities to improve operational performance through data.
• Present insights and recommendations to stakeholders across levels and functions.
• Act as a trusted analytical advisor to leadership.
• Establish and document metric definitions and reporting standards.
• Ensure consistency and accuracy across dashboards and reports.
• Improve analytical frameworks as business needs and Support operations evolve.
• Promote best practices in analytics, data visualization, and governance.

What You Will Bring

• 3+ years of experience in a statistical or data analytics role, ideally supporting a Support or Operations organization.
• Strong foundation in statistical analysis, including hypothesis testing, regression, forecasting and trend analysis.
• Hands-on experience with data visualization tools (e.g., Tableau, Power BI, Looker, or similar).
• Proficiency in SQL for data extraction and analysis.
• Experience with Python or R for advanced statistical modeling.
• Ability to work with large, complex datasets and draw meaningful conclusions.
• Strong communication skills with the ability to explain analytical findings to non-technical audiences.
• Ability to work effectively across global teams, with strong initiative to independently identify data owners, track down information, and build cross-functional relationships.
• Bachelor’s degree in Statistics, Mathematics, Data Science, Analytics, or a related field.

Preferred Qualifications

• Experience analyzing support or customer service data (e.g., case management systems, CRM platforms.
• Familiarity with support KPIs such as productivity, SLA attainment, backlog aging, TTR, NPS and CSAT.
• Exposure to data modeling, data warehousing concepts, or ETL processes.
• Experience influencing stakeholders and driving change through insights.

Work…