As an Applied Data Scientist, you will work closely with our data engineers, research scientists, and software engineers to develop and implement advanced machine learning models and algorithms. You will play a key role in leveraging data-driven insights to enhance Cognytes products and provide valuable solutions to our customers. This position offers an exciting opportunity to contribute to cutting-edge AI technologies in the fields of NLP, computer vision, pattern recognition, Large Language Models (LLMs), and more.

Responsibilities

- Develop, implement, and optimize machine learning models and algorithms, including but not limited to LLM-related AI applications.
- Collaborate with data engineers to design and implement data processing pipelines for productive model training and inference.
- Fine-tune pre-existing models and customize them to specific domains and customer requirements.
- Conduct experiments and analyze model outputs to evaluate their performance and identify areas for improvement.
- Stay up to date with the latest advancements in machine learning and AI research, and identify opportunities to leverage emerging techniques and technologies.
- Communicate and present technical findings, insights, and recommendations to both technical and non-technical stakeholders.

Your toolbox / Requirements

- MSc degree in Computer Science, Data Science, or a related field.
- 5+ years of relevant experience as a Data Scientist, applying machine learning techniques in practical projects.
- Solid understanding of machine learning algorithms and techniques, with hands-on experience in developing and implementing models.




- Proficiency in Python and experience with machine learning frameworks such as TensorFlow or PyTorch.
- Hands-on experience with supervised fine-tuning (SFT) and parameter-efficient fine-tuning methods such as LoRA and QLoRA for adapting large language models.
- Knowledge of advanced model architectures and fine-tuning approaches, including Mixture of Experts (MoE), model evaluation, and optimization.
- Hands-on experience designing and implementing LLM-based agents and multi-agent systems for planning, reasoning, tool use, task orchestration, and workflow automation.
- Experience with agentic AI frameworks such as LangGraph, AutoGen, CrewAI, or Semantic Kernel, including evaluation, observability, and production integration.
- Familiarity with data preprocessing techniques, feature engineering, and model evaluation metrics.
- Knowledge and experience in mobile network protocols, topology, and network intelligence would be an advantage.
- Knowledge and experience in applying graph algorithms to identify relevant subgraphs and connectivity patterns.
- Strong collaboration skills with demonstrated ability to work effectively across teams.
- Strong problem-solving skills and the ability to apply analytical thinking to complex business problems.
- Strong attention to detail and the ability to work effectively in a fast-paced, collaborative environment.
- Willingness to travel abroad (10%).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Applied Data Scientist (Pune)
🏢 Cognyte Analytics India
📍 Pune