SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Axonius is seeking a Senior Cyber Data Analyst to join the Asset Intelligence Research team. In this role, you will lead end-to-end research projects that directly enhance the Axonius asset intelligence platform, which helps enterprise customers discover, classify, and secure their entire IT asset inventory.
You will conduct research on asset data quality, fidelity assessment, enrichment, and correlation across device, identity, software, and SaaS asset types. Working closely with Product and Engineering teams, you will transform technical research into production-ready product capabilities. Your work will focus on defining gating conditions that evaluate assets across three dimensions: existence, classification, and risk/criticality assessment.
Key responsibilities include:
- Leading end-to-end research projects on asset data quality, enrichment, and correlation
- Building data analysis pipelines using Python and SQL to automate asset research
- Prototyping enrichment and classification logic
- Researching and defining asset evaluation criteria across multiple dimensions
- Partnering with Product and Engineering to convert research into product features
- Utilizing AI/LLM tools to accelerate data analysis and research output
About Axonius: The company transforms cyber asset intelligence into actionable insights. The Axonius Asset Cloud integrates data from every system in an organization's IT infrastructure, helping Security, IT, and GRC teams optimize risk, performance, and cost. The platform covers cyber assets, software, SaaS applications, identities, vulnerabilities, and infrastructure. Axonius is cited as one of the fastest-growing cybersecurity startups with recognition from CNBC, Forbes, and Fortune.
REQUIREMENTS:
Minimum Qualifications:
- 4+ years of professional experience in security research, cyber asset management, threat intelligence, or security data analysis
- Demonstrated proficiency with Python for scripting/automation and SQL for querying complex, large-scale security datasets
- Hands-on experience integrating AI/LLMs into technical workflows to accelerate data analysis, parsing, or research output
- Practical understanding of security data sources and their signal quality (EDRs, MDMs, CMDBs, network scanners, cloud providers, SaaS management tools) and ability to reason about reliability of each
Preferred Qualifications:
- Prior experience in B2B SaaS or enterprise cybersecurity product environments
- Experience in cybersecurity asset management (CSAM), IT asset management (ITAM), or cyber asset attack surface management (CAASM)
- Experience designing asset fidelity or criticality scoring logic combining signals across multiple data sources
- Proven track record of framing open-ended security data problems into scalable software feature requirements
