This is a remote position.
Mid-Cyber Security Analyst - Remote Job, 2-3+ Year Experience
Annual Income: $86K - $110K
A valid work permit is necessary in the US
About us: Patterned Learning is a platform that aims to help developers code faster and more efficiently. It offers features such as collaborative coding, real-time multiplayer editing, and the ability to build, test, and deploy directly from the browser. The platform also provides tightly integrated code generation, editing, and output capabilities.
Responsibilities:
- Identify vulnerabilities within our systems, particularly focusing on CorVel systems.
- Generating an excellent caliber of customer-facing security reports
- Performing proactive threat hunting across customer and company environments
- Assisting in the creation of threat detection analytics/use cases
- Performing quality checks and assisting with workload management for junior analysts
- Acting as an escalation point for the internal shift and supporting all customers
- Implement new processes and procedures as well as identify opportunities for improvement
- Providing customer training on how to use the SenseOn platform
- Mentoring and developing junior analysts within the team
Requirements:
- Understanding of networking infrastructure, protocols, and topology (Essential)
- Experience with SIEM, MDR, EDR, and vulnerability management tools (Must)
- Proficient in the use of Structured Query Language (SQL) (Must)
- Experience as shift lead (Desirable)
- Strong knowledge of the MITRE ATT&CK and D3FEND frameworks
- Strong knowledge of OS fundamentals and security hardening methods
- Strong customer-facing experience both verbal and written (Essential)
- Great analytical skills and attention to detail
- Excellent communication skills both written and verbal
- You are a team player, with a strong sense of purpose and have high integrity
Why Patterned Learning LLC?
Patterned Learning can provide intelligent suggestions, automate repetitive tasks, and assist developers in writing code more effectively. This can help reduce coding errors, improve productivity, and accelerate the development process.
The pattern recognition is particularly relevant in the context of coding. Neural networks, especially deep learning models, are commonly employed for pattern detection and classification tasks. These models simulate human decision-making and can identify patterns in data, making them well-suited for tasks like code analysis and generation.