We’re looking for an exceptional Data Scientist to join our team and help turn complex infrastructure, workload, and performance data into actionable intelligence. In this role, you’ll work closely with engineering, product, and customer-facing teams to analyze large-scale data systems, identify patterns, and develop models and insights that directly improve our platform and customer outcomes.

This is a high-impact role for someone who wants to work on real-world problems at the intersection of data, cloud infrastructure, and machine learning.

What You’ll Do

• Analyze large-scale workload, infrastructure, and performance data from customer environments
• Develop statistical models, analyses, and experiments that improve our optimization engine
• Identify patterns in workload behavior, resource usage, runtime performance, failures, and more
• Collaborate with engineering and product teams to translate data insights into product capabilities
• Build dashboards, reports, and internal tools that help teams understand product performance and customer impact
• Evaluate model performance and help define success metrics for optimization, reliability, and cost reduction
• Support customer-facing analyses that demonstrate savings, performance improvements, and infrastructure opportunities
• Help establish best practices for experimentation, data quality, and analytical rigor

What We’re Looking For

We work with complex, high-volume infrastructure and workload data. You should be comfortable analyzing messy real-world datasets, asking sharp questions, and translating your findings into practical product and business impact.

Specifically, we’re looking for candidates who have:

• At least 3 years of proven experience in data science, analytics, applied statistics, or a related field
• Strong proficiency in Python and common data science libraries such as pandas, NumPy, scikit-learn, or similar
• Strong SQL skills and experience working with relational databases
• Experience analyzing production systems, time-series data, performance data, or operational datasets
• Strong statistical thinking and experience designing experiments or evaluating model outcomes
• Ability to communicate complex analysis clearly to technical and non-technical audiences
• Strong product sense and ability to connect data insights to customer value

Nice to Have

• Experience with cloud infrastructure, Databricks, Spark, Kubernetes, or distributed systems
• Experience with forecasting, anomaly detection, or workload modeling
• Experience building ML models for operational decision-making

Why Zipher?

• A team that values strong technical craftsmanship, clear thinking, and initiative
• Join early and shape the technical direction of the company
• High ownership, high trust, and meaningful impact from day one