Pure Storage · Santa Clara, California
Skills: Python, SQL, Accessibility
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 As a Data Scientist within the Hyperscale line of business, you’ll lead high-impact hardware and systems analytics initiatives, transforming rich telemetry from Everpure’s FlashArray and FlashBlade hardware and software into rigorous predictive models, causal insights, and strategic product metrics. You’ll apply advanced statistical and quantitative research methods to complex platform and time-series data—not traditional business metrics—to help engineering and leadership understand fleet health, reliability, and performance and make better product and roadmap decisions. The core of the role is turning rigorous analysis into clear, actionable recommendations. You’ll work closely with hardware, software, and support teams to connect what our systems do in the field with how we design, test, and improve them. Because the questions evolve in a fast-moving analytics organization, we’re looking for someone who brings strong research rigor and adapts it to the problem at hand. You’ll join an inclusive, collaborative team that values diverse backgrounds, perspectives, and career paths. WHAT YOU'LL DO Advanced Predictive & Statistical Modeling: Develop ML models spanning predictive modeling, time-series prediction, clustering, churn reduction, anomaly detection, and recommendation systems. Quantitative Research: Apply advanced computational methods and statistical techniques, including multilevel models and Statsmodels,…
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