layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Security Research Engineer, Attack Surface & Risk Signals at CyberCube

Design Risk Signals: Develop innovative, quantitative signals that accurately measure a company’s exposure to cyber attacks based on their network architecture, asset configurations, and internet footprint.
Quantify the Unquantifiable: Translate theoretical cybersecurity concepts and complex network topologies into empirical, actionable risk metrics and assumptions.
Architectural Deep-Dives: Evaluate and extract meaningful insights from how organizations deploy and configure internet-facing protocols, cloud infrastructure, and enterprise networks.
Threat Landscape Research: Conduct in-depth research on emerging cyber threats (e.g., critical vulnerabilities, ransomware, trending exploits, data breach techniques) and map them to underlying asset configurations.
Cross-Functional Collaboration: Serve as the subject matter expert on internet architecture, working closely with product, analytics, and engineering teams to integrate your risk signals into production models.
Must-Have Skills & Qualifications
Deep Internet & Networking Expertise: Expert-level understanding of how the internet works at a foundational level. You should be intimately familiar with network protocols (TCP/IP, BGP, DNS, HTTP/S, TLS), routing, ASN ecosystems, and complex enterprise network configurations.
Strong Quantitative Acumen: Proven ability to apply mathematical and statistical concepts to real-world problems. You must be able to design quantitative metrics and build logic that scores and sizes risk exposure accurately.
Analytical Mindset: Exceptional problem-solving skills with a track record of conceptualizing complex, abstract security concepts and breaking them down into measurable data points.
Educational Background: Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a related highly quantitative/technical field.
Experience: 3–5+ years of relevant work experience in network engineering, cyber threat research, risk modeling, or a related domain.
Good-to-Have (Preferred) Skills
Coding for Signal Creation: Proficiency in Python or
R to prototype algorithms and turn your theoretical risk concepts into actual programmatic outputs.
Data Querying: Experience with SQL and relational databases to pull, manipulate, and analyze large datasets of asset and configuration data.
Big Data Exposure: Familiarity with big data frameworks (Spark / Hadoop), flat files, complex data types (JSON, XML), and working with APIs.
Industry Context: Experience working in or adjacent to the cyber insurance, risk modeling, or data science industries.
Certifications: Advanced technical or security certifications (e.g., CISSP, CISM, or advanced Cisco/networking certifications) are a plus, but hands-on expertise matters most.
Who might thrive here

Security Research Engineer, Attack Surface & Risk Signals

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Equal opportunity and accommodations

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