Network Data Engineer

Description

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’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.

As a Cognyter you will:

• 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.

Requirements

For that mission you will need:

• Prior experience in network traffic forensics or application traffic analysis.
• Deep understanding of network protocols (Ethernet, IP, TCP, UDP, DNS, etc.)
• Familiarity with TLS internals
• Experience working with network traffic data to extract meaningful characteristics or patterns from packet streams
• Experience using Wireshark/tshark, Network Sniffers and protocol dissectors
• Familiarity with basic ML/statistics
• Experience with Python or any other language for scripting and automation
• Attention to detail and a high standard of data handling
• Bachelor’s degree – Computer Science / Information technology
• Highly committed and responsible, independent and able to take initiative
• Flexible and easy to adapt working on multiple technical contexts
• Able to work in a dynamic environment

Nice to have:

• Research-level machine learning expertise
• AI models knowledge
• Experience creating labeled datasets and synthetic capture generation
• Experience with NoSQL databases (e.g., MongoDB)
• Experience with CI/CD solutions (e.g., Jenkins, TeamCity, Gitlab CI)
• Experience with Linux and Windows operating systems
• Understanding the SDLC – software Dev. lifecycle -> being part from designing to execution -> writing tests, executing, open bugs.
• Previous experience in a SCRUM team

Others:

• Team player
• Goal oriented
• Open personality with great communication skills
• Willing to interact and collaborate with different interfaces from around the world
• Willing to develop in a very dynamic work environment
• Fluent communication skills in English