To support HP Security Advisory Services, we are looking for an experienced Security Data Analyst who can perform advanced data analysis on security data to identify patterns, abnormal behavior and provide management insights from the data. The Security Data Analyst Leader will assist in driving new data analysis service growth for Professional Security Advisory Services. Security Advisory encompasses: WW Program Management, Cyber Security, Legal, Governance, Risk, Compliance, Audit and Cloud as it relates to cyber security for HP clients. The Security Data Analyst leader is part of a new exciting security service, diverse worldwide security team supporting the advisory team in new and existing opportunities on security data analysis services. This position will work within HP’s eco-system of professional delivery services to drive and support new business. Our objective is to grow this security service across all of HP’s customer sectors in a meaningful way. The successful candidate will be an expert in security data analysis to help the security advisory team address this specific and respective area, especially as it continues to grow.
Responsibilities:
Drive security analytics globally for HP Security advisory professional services.
Responsible for growing a new security data analysis service.
Identify and assess security risks based on the analysis of security data.
Collaborate with experts across cybersecurity, security advisory team, and IT disciplines.
Monitor data activity, reporting on security incidents/event.
Developed runbook documentation to aid in troubleshooting based on data analysis.
Education and Experience:
Experience in design, development, implementation of SIEM platforms.
5+ years of relevant experience.
Experience in information security or a related field.
Experience with computer network penetration testing and techniques.
Knowledge and Skills:
Demonstrated ability of analytical expertise, close attention to detail & critical thinking
Ability to identify new opportunities to mature security by analyzing patterns in data.
Excellent problem-solving, analytical & communication skills.
Ability to identify and mitigate network vulnerabilities and explain how to avoid them.
Excellent oral & written technical communication skills.
Proficiency in data analysis tools and software (e.g., SQL, Python, R).
Machine learning algorithms expertise to analyze data and identify patterns.
Experience in natural language processing.
Developing intelligent systems that can learn from.
Integrating AI technologies into existing systems and processes.
Leveraging AI technologies and their potential applications to improve automation.
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