Computer Science Graduates, Postgraduates Vacancy at Dell

Overview:

Dell is hiring an experienced Senior Analyst-Data Science at their Bangalore location. As a Sr. Analyst, you will have a crucial role in shaping our data-driven decision-making process. This role involves applying advanced knowledge of Generative AI models, Large Language Models (LLMs), Deep Learning, and Reinforcement Learning principles. The candidate will be required to develop impactful data models and predictive algorithms, create compelling recommendations based on data insights, lead partnerships with the academic and business community, and influence strategic decisions.

The complete details of this job are as follows:

Roles and Responsibilities:

• Design and implement machine learning models, including generative models and large language models (LLMs), and deep learning architectures.
• Design, develop, and program methods, processes, and systems to consolidate and analyze unstructured data, generating actionable insights and solutions.
• Analyze complex datasets, identify patterns, and use statistical analysis to validate data and ensure the accuracy of the models.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, and other business outcomes.
• Collaborate with cross-functional teams to understand their needs and devise possible solutions using data modeling and analysis.

Preferred Skills:

• Bachelor’s, Master’s in Computer Science, Data Science, Statistics, or a related field.
• 3-5year of experience as a Senior Data Scientist or similar role in a data-driven environment.
• Deep understanding of Generative AI models, Large Language Models (LLMs), Deep Learning, and Traditional Machine Learning.
• Experience with machine learning frameworks (PyTorch) and libraries.
• Proficient in programming languages such as Python

Desirable Skills:

• Certifications in AI, ML, Kubernetes, or cloud environments are a plus.
• Experience with CI/CD pipelines, Jenkins, Git, or similar tools. Familiarity with MLOPs techniques and framework

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