- Investigate advanced and persistent attacks using data analysis and data science tools
- Analyze customers' web traffic to detect unidentified threats and reduce false positives using Elasticsearch and BigQuery
- Research, design, and continuously enhance detection mechanisms to stay ahead of evolving threats
- Provide real-time technical support to global customers, delivering professional and timely incident responses
- Produce clear, insightful incident reports
- Collaborate cross-functionally with R&D and Research teams to optimize the company's detection and mitigation capabilities
- Design, plan, and implement internal automation projects to improve team efficiency
- Work in a shift-based schedule, including weekends
- At least 3 years of experience in data analysis in cybersecurity or fraud detection domains, including experience with logs and dashboards
- Strong SQL skills: complex queries, aggregations, GROUP BY, ORDER BY, filters, window functions (e.g., RANK()), CTEs, and subqueries
- Technical understanding of web technologies and client–server architecture (APIs, HTTP, basic HTML/JavaScript)
- Experience working with web traffic data, including HTTP traffic, logs, request analysis, and traffic pattern investigation.
- Experience with SIEM systems (experience with the Elastic Stack would be an advantage)
- Strong troubleshooting and problem-solving skills
- Experience in customer support, including direct communication with clients; professionalism and politeness are essential
- Strong English communication skills
WOULD BE A PLUS
- Experience in a Cybersecurity Analyst/Researcher role, ideally supporting external customers in threat detection and response, providing web application security, bot management, fraud detection.
- Experience with research methodologies (hypothesis testing, verification and research plan)
- Python and JavaScript knowledge
- Experience with BigQuery/Snowflake
- Proficiency in building dashboards using BI tools (Snowflake, Looker, Kibana, JSM)