Experience

Responsibilities:

• Designed and fine-tuned detection rules in Microsoft Sentinel (KQL) and Google Chronicle to enhance alert fidelity and minimize false positives.
• Researched emerging threats and developed proactive detection content to strengthen organizational threat coverage and readiness.
• Worked across multiple SIEM platforms, gaining practical experience and broadening expertise in detection engineering across varied environments.
• Contributed to continuous improvement of detection logic, including rule lifecycle management and performance tuning.
• Supported the development of detection content pipelines and detection-as-code practices, driving scalability, standardization, and consistency.

Learning Experience:

• Enhanced ability to balance detection fidelity and false positive reduction for real-world SOC efficiency.
• Developed cross-platform SIEM expertise, enabling adaptability in diverse enterprise environments.
• Gained experience in operationalizing threat intelligence into actionable detection rules.
• Learned the importance of lifecycle management and continuous improvement in detection engineering.
• Built understanding of scalable detection engineering practices through detection-as-code methodologies.

Skills:

• Google Chronicle
• Threat Detection
• Correlation Logic
• YARAL
• Sigma Rule
• Threat Research
• Detection-as-Code: pipeline development, YAML/JSON-based rule management

Responsibilities:

• Administrator Endpoint Security with expertise in implementing and managing cutting-edge cybersecurity solutions.
• Proficient in utilizing EDR (Endpoint Detection and Response) tools to proactively identify and respond to potential security threats.
• Extensive experience in leveraging SIEM (Security Information and Event Management) systems to collect and analyze security event logs, facilitating early threat detection.
• Skilled in conducting thorough threat hunting exercises to identify advanced and persistent threats that may evade traditional security measures.
• Actively monitored security trends and emerging threats, continuously improving security posture by implementing appropriate countermeasures.
• Proactively identified and addressed emerging threats by leveraging threat intelligence, conducting in-depth investigations, and implementing targeted countermeasures, ensuring a resilient and secure endpoint environment.
• Worked to identify, prioritize, and remediate security vulnerabilities in the infrastructure.

Learning Experience:

• Interacting with international colleagues and clients.
• Deep knowledge on the basic topics.
• How to handle urgent and important tasks on a short notice.
• Leading teams into performing with optimal efficiency.
• Planning the course of the projects and prioritizing tasks.
• How to work with experienced and senior authorities.
• Importance of learning in every possible situation.
• Handling and mitigating high priority threats and incidents.
• Resolving issues with optimal thinking and timely delivery.

Skills:

• Fostering Inclusivity
• Cybersecurity Incident Response
• Communication
• Security Operations
• Application Security
• Azure Sentinel
• Advanced Threat Analytics (ATA)
• Linux
• Azure AD
• EDR
• SentinelOne
• Security Incident Response
• Cyber Security
• SIEM
• Root Cause Analysis
• Microsoft Azure
• Endpoint Security
• Azure Active Directory
• Palo Alto Networks Prisma
• Security Operations Center
• Tenable Nessus
• DarkTrace

Responsibilities:

• Worked on a project which is a patent now : MACHINE LEARNING BASED SYSTEMS AND METHODS FOR IDENTIFICATION OF TRANSACTION CATEGORY FROM CODED ERP DATA.
• Designed and implemented a Python module to assess incoming data for suitability in predictive modeling, ensuring high-quality inputs.
• Led Time Series Analysis initiatives, leveraging advanced techniques to extract valuable insights from temporal data.
• Pioneered a statistical methodology employing power transformations, effectively identifying outliers and automating data trimming processes, leading to more robust analysis outcomes.
• Elevated transactional analysis by streamlining and automating reporting procedures, enhancing the efficiency and accuracy of insights generated.
• Spearheaded efforts to optimize the runtime performance of prediction modules, resulting in substantial gains in processing speed and efficiency.
• Focused on enhancing the collections summary report, introducing a module incorporating cut-off frequency and Machine Learning principles to deliver more comprehensive and actionable summaries.

Learning Experience:

• First-hand experience of corporate environment.
• Know-how of working in a company.
• How to attend and take part in meetings.
• Team work and group discussion on making decisions.
• Planning for a project/work.
• Distribution of work for better efficiency.
• Importance of on-time completion of work.

Skills:

• Python (Programming Language)
• Data Science
• Machine Learning