The composable, out-of-the-box data architecture that gives organizations complete freedom to build, adapt, and scale any data workload — from legacy databases to real-time AI pipelines — without vendor lock-in. Backed by Insight.
About the role
• Formulate and apply mathematical and statistical models to evaluate the performance of NexusOne's cross-estate data orchestration layer, identifying optimization opportunities across identity management, governance enforcement, and data pipeline execution. • Define data requirements, gather and validate quantitative information from NexusOne's operational environment, and apply statistical methods to assess platform performance, pipeline throughput, and governance policy compliance across client deployments.
What they're looking for
- • Bachelor's degree in Computer Science, Engineering, Business Analytics, or a related field that develops analytical, logical, reasoning, and problem-solving skills
- • Experience in the information technology industry applying quantitative and analytical methods to operational or data platform challenges
- • Working knowledge of statistical analysis and mathematical modeling techniques as applied to data systems and platform performance evaluation
- • Ability to translate quantitative findings into clear recommendations for both technical and non-technical stakeholders
- • Master's degree in Business Analytics or a related discipline
- • Experience transforming legacy infrastructure into scalable Spark/Airflow environments to support real-time analytical workloads
More about this role
You don't have an AI story if you don't have your data story. That's where NexusOne comes in.
We're the converged data platform for the AI era — composable by design, built on an open-source foundation, and AI-native from the ground up. One identity, one governance envelope, one operational layer across every mainframe, data lake, warehouse, and streaming system in the business. For the first time, enterprises can bring their existing stack along instead of rebuilding it — and still give AI agents full context across the estate.
What we stand for is simple: sovereign data, interoperable systems, decoupled intelligence — delivered the way modern software should be. No rip-and-replace. No multi-year transformation. Our CEO Anu Jain puts it well: we turn the "ball of yarn" of data integrations into a unified engine — less like assembling car parts, more like buying the car ready to drive. 85+ open-source tools pre-integrated. AI-native automations that deploy and self-heal the stack without human toil. Forward-deployed engineers who build shoulder-to-shoulder with customer teams — hands on keyboards, not just on decks.
It's working, and fast. We're tripling revenue year over year,...
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