As a Data Science & Network Researcher at Cognyte, you will have the opportunity to work closely with data engineers, research scientists, and software engineers to develop and implement advanced AI and machine learning models. Your role will involve analyzing large-scale data generated by complex, distributed, and networked systems to derive actionable insights for enhancing Cognyte's products and providing valuable solutions to customers. You will also contribute to cutting-edge AI technologies in areas such as network traffic-based data analysis.

• *Key Responsibilities:**
• Develop, implement, and optimize AI and machine learning models and algorithms, including LLM-related applications.
• Analyze network traffic data to identify patterns, anomalies, and trends, and apply AI and machine learning techniques to derive actionable insights.
• Collaborate with data engineers to design and implement scalable data processing pipelines that support efficient model training and inference.
• Fine-tune pre-existing models and adapt them to specific domains and customer requirements.
• Conduct experiments, analyze model outputs, and evaluate performance to identify opportunities for improvement.
• Support research workflows in distributed and production-like environments, including performance analysis and basic network troubleshooting.
• Stay updated with the latest advancements in AI, machine learning, and data-driven research to identify opportunities for applying emerging technologies.
• Communicate and present technical findings, insights, and recommendations to technical and non-technical stakeholders.
• *Qualifications Required:**
• MSc or PhD degree in Computer Science, Data Science, or a related field.
• 3+ years of relevant experience as a Data Scientist or Researcher, applying AI and machine learning techniques in research or applied projects.
• Strong understanding of machine learning algorithms and methodologies with hands-on experience in developing and deploying models.
• Good understanding of networking concepts including IP addressing, TCP/IP, ports, latency, and packet flows.
• Proficiency in Python and experience with machine learning frameworks such as TensorFlow or PyTorch.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Hands-on experience or exposure to analyzing and debugging network-related data in distributed or large-scale systems.
• Familiarity with network and system troubleshooting tools such as Wireshark, Tcpdump, ping, traceroute, netstat, or ss.
• Strong collaboration skills and ability to work effectively across multidisciplinary teams.
• Strong analytical and problem-solving skills with the ability to reason about complex systems and datasets.
• High attention to detail and ability to work effectively in a fast-paced, research-driven environment.
• Willingness to travel abroad (10%).

Cognyte is a values-driven business with a strong passion for innovation, making a meaningful impact on the world. They are seeking curious minds like you, who are eager to break new ground and bring innovative ideas to life. If this resonates with you, consider applying to be part of Cognyte's dynamic team. As a Data Science & Network Researcher at Cognyte, you will have the opportunity to work closely with data engineers, research scientists, and software engineers to develop and implement advanced AI and machine learning models. Your role will involve analyzing large-scale data generated by complex, distributed, and networked systems to derive actionable insights for enhancing Cognyte's products and providing valuable solutions to customers. You will also contribute to cutting-edge AI technologies in areas such as network traffic-based data analysis.

• *Key Responsibilities:**
• Develop, implement, and optimize AI and machine learning models and algorithms, including LLM-related applications.
• Analyze network traffic data to identify patterns, anomalies, and trends, and apply AI and machine learning techniques to derive actionable insights.
• Collaborate with data engineers to design and implement scalable data processing pipelines that support efficient model training and inference.
• Fine-tune pre-existing models and adapt them to specific domains and customer requirements.
• Conduct experiments, analyze model outputs, and evaluate performance to identify opportunities for improvement.
• Support research workflows in distributed and production-like environments, including performance analysis and basic network troubleshooting.
• Stay updated with the latest advancements in AI, machine learning, and data-driven research to identify opportunities for applying emerging technologies.
• Communicate and present technical findings, insights, and recommendations to technical and non-technical stakeholders.
• *Qualifications Required:**
• MSc or PhD degree in Computer Science, Data Science, or a related field.
• 3+ years of relevant experience as a Data Scie