Develop ML Models: Design, build, and deploy machine learning models for cybersecurity threat detection, anomaly detection, intrusion detection systems (IDS), malware analysis, and data classification.
Data Analysis: Work with large sets of security-related data, including logs, network traffic, and endpoint information, to identify patterns and potential threats.
Threat Intelligence: Integrate machine learning algorithms with threat intelligence sources to predict and identify emerging attack vectors and malicious behavior in real-time.
Automation: Automate the analysis of security incidents and threats using machine learning pipelines to reduce response times and human intervention.
Model Optimization: Continuously refine and improve machine learning models, ensuring they perform effectively under different cybersecurity scenarios.
Collaboration: Collaborate with cybersecurity professionals, data engineers, and other teams to integrate machine learning models into security operations and defense strategies.
Evaluation: Conduct research to evaluate emerging machine learning techniques and their application in cybersecurity, staying ahead of potential new threats and attack methods.
Reporting: Create actionable insights, reports, and dashboards based on the performance of machine learning models in detecting and mitigating threats.
Skills:
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