Digital Forensics Analyst

Today’s world is crime-riddled. Criminals are everywhere, invisible, virtual and sophisticated. Traditional ways to prevent and investigate crime and terror are no longer enough… Technology is changing incredibly fast. The criminals know it, and they are taking advantage. We know it too. For nearly 30 years, the incredible minds at Cognyte around the world have worked closely together and put their expertise to work, to keep up with constantly evolving technological and criminal trends, and help make the world a safer place with leading investigative analytics software solutions. We are defined by our dedication to doing good and this translates to business success, meaningful work friendships, a can-do attitude, and deep curiosity.As a Cognyter you will: We’re looking for an analyst to examine encrypted raw network data, extract TLS and IP-level metadata, and identify patterns or trends within complex data streams.You’ll build analysis pipelines and ensure the accuracy of detection methods using well-defined evaluation metrics.Candidates must demonstrate strong knowledge of network protocols, hands-on experience with packet capture analysis, and solid data analysis or machine learning skills.You will gain crypto domain expertise and be responsible for developing a Blockchain analytics product.For that mission you’ll need:Bachelor’s degree – Computer Science / Information technologyPrior experience in network traffic forensics or application traffic analysis.Deep understanding of network protocols (Ethernet, IP, TCP, UDP, DNS, etc.)Familiarity with TLS internalsExperience working with network traffic data to extract meaningful characteristics or patterns from packet streamsExperience using Wireshark/tshark, Network Sniffers and protocol dissectorsFamiliarity with basic ML/statisticsExperience with Python or any other language for scripting and automationFluent EnglishAttention to detail and a high standard of data handlingHighly committed and responsible, independent and able to take initiativeFlexible and easy to adapt working on multiple technical contextsAble to work in a dynamic environmentNice to have:Research-level machine learning expertiseAI models knowledgeExperience creating labeled datasets and synthetic capture generationExperience with NoSQL databases (e.g., MongoDB)Experience with CI/CD solutions (e.g., Jenkins, TeamCity, Gitlab CI)Experience with Linux and Windows operating systemsUnderstanding the SDLC – software Dev. lifecycle -> being part from designing to execution -> writing tests, executing, open bugs.Previous experience in a SCRUM team

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