Data Scientist-Artificial Intelligence

About the Role

A career in IBM Consulting involves long-term client relationships and close collaboration worldwide. You will work with leading companies across industries, helping them shape their hybrid cloud and AI journeys.

Your Role And Responsibilities

As a Data Scientist with expertise in Artificial Intelligence, you will combine data analysis and business acumen to tackle cognitive computing challenges. You will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models.

Key Responsibilities

• Design AI Solutions: Architect and deliver AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models, and experience in tools like Github Copilot and Amazon Code Whisperer.
• Develop Cognitive Solutions: Create comprehensive cognitive solutions that process and analyze structured and unstructured data, utilizing expertise in NLP, ML, and specialized areas such as Image Processing, Video Processing, Voice Processing, or Watson technologies.
• Implement AI Frameworks: Apply strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face, to develop and deploy AI models.
• Manage AI Project Lifecycle: Oversee the full AI project lifecycle, from research and prototyping to deployment in production environments.
• Collaborate with Stakeholders: Work with stakeholders to identify business problems and leverage artificial intelligence for cognitive computing, driving business value through AI-driven solutions.

Qualifications

Preferred Education: Master's Degree

Technical And Professional Expertise

• Advanced Analytics Techniques: Exposure to advanced analytics techniques for structured data, including data analysis and interpretation.
• AI Frameworks and Tools: Experience working with AI frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face, and tools like Github Copilot and Amazon Code Whisperer.
• Programming Skills: Proficiency in Python programming language.
• NLP and ML Methods: Exposure to Natural Language Processing (NLP) and Machine Learning (ML) methods for unstructured content, including foundation models and large language models.
• Cloud Platforms and Databases: Experience working with cloud platforms (e.g., Kubernetes, AWS, Azure, GCP) and related services, as well as relational and NoSQL databases (SQL, Postgres, DB2, MongoDB).

Preferred Technical And Professional Experience

• Familiarity with Modern UI frameworks such as Backbone.js, AngularJS, React.js, Ember.js, Bootstrap, and JQuery.
• Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib.
• Experience working with various operating systems (Linux, Windows, iOS, Android).