IBM internship Data Scientist

Introduction to IBM Consulting

A career in IBM Consulting fosters long-term client relationships and global collaboration. You'll engage with leading companies, guiding their hybrid cloud and AI transformations. Supported by strategic partners, robust IBM technology, and Red Hat, you'll have the resources to drive significant change. At IBM Consulting, curiosity fuels success, encouraging new ideas and innovative solutions. Our culture prioritizes growth, empathy, and your long-term career development while valuing diverse skills and experiences.

Your Role And Responsibilities as an IBM internship Data Scientist

As an IBM internship Data Scientist specializing in Artificial Intelligence, you will adeptly combine data analysis with business acumen to address cognitive computing challenges. You will be responsible for architecting and delivering cutting-edge AI solutions, with a strong emphasis on foundation models and large language models.

• Assist with AI Solution Development: Participate in designing and delivering AI solutions using advanced technologies, focusing on foundation models and large language models. You will learn to apply advanced analytics for structured data and explore Natural Language Processing (NLP) and Machine Learning (ML) for unstructured content.
• Explore AI Tools and Technologies: Engage with tools like Github Copilot and Amazon Code Whisperer to develop comprehensive cognitive solutions for both structured and unstructured data.
• Support AI Project Lifecycle: Contribute to the full AI project lifecycle, from research and prototyping to production deployment, under the guidance of senior team members.
• Learn AI Frameworks and Libraries: Familiarize yourself with AI frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face, and learn to use libraries like SciKit Learn, Pandas, and Matplotlib.

Required Technical And Professional Expertise

• Develop and deliver AI-driven solutions leveraging foundation models and large language models.
• Apply advanced analytics and machine learning techniques to structured and unstructured data.
• Design and implement end-to-end AI systems, from research and prototyping to production deployment.
• Collaborate with cross-functional teams to identify business opportunities for AI and cognitive computing.
• Utilize modern AI-assisted tools such as GitHub Copilot and Amazon CodeWhisperer to enhance productivity.
• Develop and optimize NLP, image, video, or voice processing models as required.
• Work with a variety of data sources and architectures, including relational and NoSQL databases.
• Ensure scalability, performance, and reliability of deployed AI solutions across cloud platforms.

Key skills/competency

• Data Science
• Artificial Intelligence
• Machine Learning (ML)
• Natural Language Processing (NLP)
• Foundation Models
• Large Language Models (LLMs)
• Advanced Analytics
• Python
• TensorFlow/PyTorch
• Cloud Platforms