# Operations Research / Data Platform Engineer at Nexus Cognitive

- Company: Nexus Cognitive
- What the company does: 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.
- Company website: https://www.nexuscognitive.com/
- Type: Startups
- Level: Mid level
- Location: Atlanta HQ
- Work setup: Remote
- Posted: 2026-07-02
- Apply by: 2026-10-08
- Apply: https://jobs.ashbyhq.com/nexus-cognitive/b8730188-439f-4908-8fff-c5ad47befe4c
- Page: https://www.1752.vc/careers/jobs/nexus-cognitive-operations-research-data-platform-engineer/

## 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

Tags: Product Engineering