AI & Automation Data Analyst

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem.

This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.

THE ROLE

Everpure is moving from an application-centric world to a data-centric one — where AI depends on trusted, well-governed, and contextualized data across the business. As part of this shift, we're looking for a Staff Analyst, AI & Automation to lead the technical build of AI and applied ML capability inside the analytics function.

This is an individual contributor role — you will not manage people. Your leverage comes from what you build and ship: AI agents, applied ML models, and automated analytics workflows that change how insight gets produced, working closely with cross-functional teams to bring these to life.

AI is changing by the week, not by the year. We're not looking for someone who adopts AI once it's already mainstream — we want someone who is naturally ahead of the curve: scanning what's new, testing it quickly, and bringing it into the team before it's obvious to everyone else. This role has real freedom to experiment, rethink existing approaches, and change course as the field moves.

WHAT YOU'LL DO

• Own the technical build of AI-powered analytics tools — including RAG pipelines, LLM-assisted querying, agent workflows, and applied ML models. Our current stack includes Glean, Gemini, Claude Code and Snowflake Cortex, and we expect that to change; we care more that you pick up new tools quickly than that you already know ours.
• Apply data science methods (forecasting, segmentation, anomaly detection, classification) where a problem genuinely calls for them — though the core of this role is LLM- and agent-based automation rather than classical modelling.
• Design, build, and deploy AI agents for analytics use cases — e.g. agents that answer business questions from data, auto-generate insights, flag anomalies, or draft recurring reports without manual pull.
• Identify and prioritize high-value opportunities to automate manual, repetitive analytics work with AI, and independently prototype, test, and productionize those solutions.
• Propose and maintain a rolling technical roadmap for AI and data science work in the analytics function — a living document you revisit and adjust as the field moves, not a fixed annual plan.