The Operations Research Analyst/Data Platform Engineer applies mathematical modeling, statistical analysis, and systems optimization techniques to support the development, deployment, and operational performance of the NexusOne (NX1) data platform and its client delivery engagements. NexusOne is a universal data control plane that orchestrates an organization's entire data estate - spanning legacy on-premises systems, cloud warehouses, and hybrid environments - through a unified identity model, governance envelope, and operational layer. **Key Responsibilities** • 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. • Present the results of mathematical modeling and data analysis to client stakeholders and delivery leadership, translating quantitative findings into platform configuration recommendations and operational decisions. • Collaborate with engineering and client delivery teams to identify and solve complex data operational problems - including legacy system modernization, AI pipeline readiness, and cross-estate governance gaps - using NexusOne as the enabling platform. • Prepare technical and management reports evaluating data operational problems, analyzing solution alternatives, and recommending NexusOne configurations that meet client performance, compliance, and AI readiness requirements. **Minimum Qualifications** • 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. **Preferred Qualifications** • 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. • Experience delivering data products that reduce operational latency and cost while enabling data-driven decision-making. • Familiarity with Infrastructure as Code practices supporting process optimization and automation.