AI Data Scientist

Stott and May; Oxford; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A dynamic healthtech startup in the UK is on the lookout for an experienced AI Data Scientist. This role involves shaping backend systems for secure data flows and AI insights, working within a collaborative team to tackle healthcare challenges. Ideal candidates should have 5+ years of experience with data science, particularly with large language models. The position promotes a hybrid working model, allowing flexibility while contributing to innovative healthcare solutions.

Qualifications

• 5+ years of experience in data science or machine learning.
• Expertise in large language models and generative models.
• Strong statistical and experimental design skills.

Responsibilities

• Design experiments with large datasets.
• Analyze reliability and bias of LLM outputs.
• Develop metrics for model performance.

Skills

Python

Data science

Machine learning

Statistical analysis

LLM expertise

Tools

PyTorch

HuggingFace Transformers

LangChain

AWS

GCP

Azure

Job description

We're working with a fast-growing, VC-backed healthtech startup on a mission to build a platform that blends human insight with advanced AI for personalised, continuous care. As part of this growth, they’re looking for an AI Data Scientist to work within a distributed team, on a hybrid model.

Your Impact

As one of their earliest AI hires, you'll shape the backend foundation powering secure data flows, AI-driven insights, and provider tools. Expect hands-on ownership in a collaborative, mission-focused team tackling real-world health challenges.

Key Responsibilities

• Design and execute experiments using large datasets, including LLM-generated or LLM-augmented data
• Analyze and validate the reliability, consistency, and bias of LLM outputs across healthcare use cases
• Fine-tune and evaluate LLMs (e.g., OpenAI, Claude, Llama) while managing risks like overfitting and hallucination
• Build scalable pipelines to preprocess, structure, and extract insights from unstructured or semi-structured data
• Work closely with clinicians and product teams to align AI insights with real-world healthcare needs
• Develop metrics and evaluation strategies for model performance, safety, and explainability
• Investigate and mitigate risks related to synthetic data and model-induced artifacts
• Help shape how healthcare AI tech can be safe, fast, and deeply human

What You'll Bring

• 5+ years of experience in data science or machine learning, including work with LLMs or large generative models
• Deep understanding of LLM internals-tokenization, attention mechanisms, fine-tuning, prompt engineering, embeddings
• Strong Python skills, including libraries like PyTorch, HuggingFace Transformers, LangChain, or similar
• Hands-on experience fine-tuning models or building applications with LLM-generated data
• Strong statistical and experimental design skills, especially around model evaluation and failure analysis
• Familiarity with cloud-based ML pipelines (e.g., AWS/GCP/Azure), versioned datasets, and reproducible experimentation
• Experience navigating data quality issues-bias, hallucination, inconsistency

For further details and immediate consideration, please get in touch.