Data Scientist
Build and deploy generative AI models using Python, TensorFlow, and cloud platforms; lead GenAI projects from ideation to production for enterprise clients.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Middle
- Employment
- Part time
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Full description
This is a free training course followed by the potential for a role with one of our clients.
Title: Data Scientist
Job location: Remote, UK (1 day per fortnight in London or Manchester)
Description:
These job roles are linked directly to free education, and upon completion of our course, you will be equipped to start your new role.
WHAT ARE WE LOOKING FOR?
- 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
THE ROLE:
Our clients are looking for Data Scientists to join their team.
KEY RESPONSIBILITIES:
- 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.
KEY REQUIREMENTS:
- 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