Senior Data Analyst

Job Profile: Analyze large datasets related to operational technology (OT) security vulnerabilities and develop data-driven insights to enhance cybersecurity products and solutions. Drive data quality improvements and conduct analytical experiments to strengthen vulnerability management systems. Key Responsibilities: • Analyze large datasets related to OT security vulnerabilities and threat intelligence • Develop data-driven insights and recommendations to improve cybersecurity products • Ensure data quality for vulnerability databases and recommend systematic improvements • Conduct experiments and statistical analysis to improve data quality and accuracy • Design and implement automated data processing workflows for security datasets • Create comprehensive reports and visualizations for stakeholders and management • Collaborate with security teams to identify patterns and trends in vulnerability data • Support the development of predictive models for threat assessment and risk analysis • Maintain and optimize data pipelines for real-time security monitoring Desired Qualification and Experience: • Education: Bachelor's or Master's degree in Engineering - Computer Science, Data Science, Cybersecurity, Information Technology, or related field • Experience: 8-10 years of professional experience working as a data analyst in data-driven projects with focus on security or cybersecurity domains Technical Skills: • Data Analysis: Strong proficiency in Python, R, SQL, and data analyst toolset for large-scale data processing • Security Domain: Deep understanding of security and vulnerability standards (CVE, CVSS, CWE, NIST frameworks) • Automation: Experience in automation of API-based systems and data integration workflows • Database Technologies: Proficiency in working with vulnerability databases, threat intelligence feeds, and security data repositories • Visualization: Experience with data visualization tools (Tableau, Power BI, matplotlib, seaborn) • Statistical Analysis: Strong foundation in statistical methods, hypothesis testing, and experimental design • Network Protocols: Knowledge of network discovery protocols and OT/IT network architectures • Asset Management: Understanding of asset description norms, formats, and industrial control system standards Domain Knowledge: • OT Security: Understanding of operational technology environments, industrial control systems (ICS/SCADA), and OT-specific vulnerabilities • Vulnerability Management: Experience with vulnerability assessment processes, threat modeling, and risk prioritization • Compliance Standards: Knowledge of cybersecurity frameworks and standards (ISO 27001, NIST, IEC 62443) • Threat Intelligence: Understanding of threat intelligence feeds, indicators of compromise (IoCs), and threat landscape analysis Collaboration and Soft Skills: • Stakeholder Engagement: Openness to collaborate with diverse teams including P-CERT, BSI (federal agency), customers, Siemens employees (product owners, experts), and standardization organizations • Communication: Excellent written and verbal communication skills to present complex data insights to technical and non-technical audiences • Global Collaboration: Ability to work effectively in global, distributed teams across different time zones • Adaptability: Flexibility to work with evolving security threats and changing regulatory requirements • Project Management: Ability to manage multiple data analysis projects simultaneously and meet deadlines Preferred Qualifications: • Certifications: Relevant cybersecurity certifications (CISSP, CISM, CEH) or data science certifications • Industry Experience: Previous experience in industrial cybersecurity, critical infrastructure protection, or OT environments • Research Background: Experience in security research, vulnerability research, or academic publications in cybersecurity • Cloud Platforms: Experience with cloud-based data analytics platforms (AWS, Azure, Google Cloud) • Machine Learning: Knowledge of machine learning techniques applied to cybersecurity use cases