Data Scientist

These job roles are linked directly to free education, and upon completion of our course, you will be equipped to start your new role., Our clients are looking for Data Scientists to join their team., * Lead Generative AI Initiatives: Take technical ownership of high-profile GenAI projects, guiding initiatives from ideation, innovation, and proof of concept (PoC) through to Minimum Viable Product (MVP) and enterprise-scale deployment.

• Technical Innovation & Experimentation: Drive work within the Ideation pillar by prototyping, testing, and evaluating novel GenAI concepts and machine learning techniques to determine scalability and business value.
• Senior Collaboration & Governance: Work closely with the Chief Data Scientist to align technical strategy, receive mentorship, and ensure rigorous quality assurance across all project deliverables.
• Cross-Stakeholder Delivery: Serve as a core technical liaison between programme teams and key stakeholders to translate complex requirements into actionable AI solutions.
• High-Impact Execution: Maintain exceptional standards of technical excellence, model evaluation, and documentation on high-visibility projects spanning two major enterprise organisations., All of our courses are 100% free for all students. There are no secret or hidden fees, no payment upon completion, and no debt. We work with our partner companies to ensure this education is free for all learners.

• 1.5+ years of experience in a technology-focused role using Python
• Able to pass a technical assessment in Python, Java or Javascript

• Commitment to complete a 16-week, part-time course to develop your mid-level skills, * Full AI Project Lifecycle: Experience in managing the full AI project lifecycle, from research and prototyping to deployment in production environments. Excellent communication and stakeholder management skills.

• Advanced Analytics Techniques: Experience with advanced analytics techniques for structured data, including proficiency in Python and AI frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face.

• NLP and ML Methods: Deep understanding of Natural Language Processing (NLP) and Machine Learning (ML) methods for unstructured content, with expertise in foundation models and large language models.

• AI Solution Development: Experience in architecting and delivering AI solutions using cutting-edge technologies, including tools like GitHub Copilot and Amazon CodeWhisperer.

• Cloud Platforms and Services: Familiarity with cloud platforms (e.g., Kubernetes, AWS, Azure, GCP, IBM Cloud) and related services, as well as experience with relational and NoSQL databases (SQL, PostgreSQL, DB2, MongoDB).