Asset Intelligence Associate

Rockwell Automation•Milwaukee, WI

5d•Hybrid

About The Position

The Asset Intelligence Associate will support SecureOT's asset intelligence program by researching, validating, and maintaining data that helps customers understand product identity, vendor lifecycle status, and vulnerability exposure across operational technology environments. This research and data quality role requires comfort with detailed technical material, and the ability to turn vendor advisories, product documentation, and vulnerability reports into clear, reliable conclusions. You will report to the Team Lead, Device & Integration Research, and have a hybrid schedule working in Milwaukee, WI.

Requirements

High School Diploma or GED
Legal authorization to work in the U.S. We will not sponsor individuals for employment visas, now or in the future, for this job opening.

Nice To Haves

Typically requires 2+ years of experience researching, analyzing, and investigating information with the ability to evaluate sources, synthesize, and document findings.
Experience working with structured data, spreadsheets, documentation systems, and technical product information.
Ability to work independently, follow established processes, and collaborate across technical and non-technical teams.
Familiarity with cybersecurity vulnerability management concepts, including CVEs, affected-version analysis, and security advisories.
Experience with OT/ICS environments, asset management, data governance, taxonomy development, or investigative research.
Exposure to tools such as Jira, Confluence, SQL, Python, APIs, web scraping, QA processes, and AI-assisted research workflows.
Background in research-intensive disciplines such as information science, archival studies, digital humanities, philosophy, history, data governance, or related fields.

Responsibilities

Research vendor lifecycle, product identity, and vulnerability information using primary sources such as manufacturer documentation, PSIRT advisories, release notes, NVD records, and other trusted references.
Evaluate incomplete or conflicting information, document assumptions and sources, and make evidence-based recommendations about affected products, versions, models, and lifecycle status.
Validate that researched data produces accurate customer-facing results in the product, including lifecycle and vulnerability coverage.
Keep clear research records, summarize findings for technical and nontechnical audiences, and escalate ambiguous or high-risk issues for review.
Support repeatable research and data quality processes, including source tracking, review workflows, regression checks, and opportunities for responsible automation.
Collaborate with asset intelligence leads, engineers, QA, and supporting analysts to improve data accuracy, coverage, and operational efficiency.