Applied Data Scientist

About Cognyte

Role Overview

Responsibilities

• Develop, implement, and optimize machine learning models, including LLM-related AI applications.
• Design data processing pipelines with data engineers for efficient model training and inference.
• Fine-tune existing models for specific domains and customer requirements.
• Run experiments and analyze model outputs to evaluate performance and identify improvements.
• Monitor advances in machine learning and AI research and identify useful emerging techniques.
• Present technical findings, insights, and recommendations to technical and non-technical stakeholders.

Required Qualifications

• MSc degree in Computer Science, Data Science, or a related field.
• 5+ years of relevant Data Scientist experience applying machine learning in practical projects.
• Solid understanding of machine learning algorithms and hands-on model development experience.
• Proficiency in Python and experience with TensorFlow or PyTorch.
• Hands-on experience with supervised fine-tuning, LoRA, and QLoRA.
• Experience designing LLM-based agents and multi-agent systems.
• Experience with agentic AI frameworks, including evaluation, observability, and production integration.
• Knowledge of model architectures, Mixture of Experts, model evaluation, and optimization.
• Experience applying graph algorithms to identify subgraphs and connectivity patterns.
• Strong collaboration, problem-solving, analytical thinking, and attention to detail.
• Willingness to travel abroad approximately 10%.

Preferred Knowledge

• Knowledge of mobile network protocols, topology, and network intelligence is advantageous.
• Familiarity with data preprocessing, feature engineering, and model evaluation metrics.

Company Culture

• Cognyte describes itself as a values-driven, innovation-focused business offering meaningful work and collaborative relationships.