Principal Data Scientist - Healthcare
$80,000–$100,000 year
Remote · London, England, United Kingdom or GB
Job Summary
As a Principal Data Scientist at Kainos, you will be responsible for delivering large-scale, high-impact AI solutions using cutting-edge machine learning and generative AI technologies. This role involves setting the strategic direction for AI and data science practices, mentoring teams, engaging with stakeholders, and ensuring the adoption of ethical AI principles. Required qualifications include a proven track record in AI/ML delivery, deep expertise in advanced AI model development, and strong commercial acumen. Desirable skills include experience with deep learning frameworks and participation in open-source AI projects.
Required Qualifications
- Proven track record of accountability for the delivery of complex, production-grade AI/ML solutions at scale
- Demonstrable experience of technical leadership in AI delivery
- Deep expertise in developing and assuring advanced AI/ML models including time series, supervised/unsupervised learning, reinforcement learning, LLMs and agentic AI
- Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG)
- Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data
- Deep understanding of responsible AI principles, model interpretability and ethical considerations
- Ability to communicate and negotiate with C-level and senior stakeholders
- Experience in developing and executing account strategies
- Demonstrated ability to build and lead high-performing teams and wider AI and data science communities
- Strong commercial acumen with a history of influencing the commercial success of AI products and solutions
Desired Qualifications
- Experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow)
- Fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini)
- Experience with data storage for AI, vector databases, semantic search, and knowledge graphs
- Active contribution to open-source AI projects, research publications, and industry events/websites
- Familiarity with AI security, privacy, and compliance standards (e.g. ISO 42001)
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