Senior Data Scientist

ICON is a global healthcare intelligence and clinical research organisation united by a mission to bring new medicines and treatments to patients faster.

As a Senior Data Scientist at ICON, you will play a key role in designing, building and deploying advanced machine learning and generative AI solutions that move from proof of concept through to production.

What You Will Be Doing:

• Leading the design, development and validation of machine learning, NLP and large language model (LLM) solutions that address priority business challenges across clinical operations, feasibility and scientific intelligence.
• Translating complex or ambiguous business questions into well-defined analytical approaches with clear success measures and delivery milestones.
• Designing and developing retrieval-augmented generation (RAG), information extraction and agentic AI workflows using structured and unstructured clinical and operational data.
• Applying robust statistical, experimental and causal inference methods to quantify impact and support evidence-based decision-making.
• Partnering with Data and ML Engineering teams to take solutions from proof of concept into robust, monitored production services using Azure and Microsoft Fabric.
• Implementing MLOps and LLMOps practices, including model versioning, reproducible pipelines, automated evaluation, and performance and drift monitoring.
• Developing evaluation frameworks for generative AI solutions, considering areas such as accuracy, groundedness, bias, safety and cost.
• Ensuring solutions comply with ICON's regulatory and quality requirements, including GxP/GCP, 21 CFR Part 11, GDPR and HIPAA.
• Contributing to responsible AI practices, including model documentation, validation evidence and assessment of third-party and vendor technologies.
• Acting as a trusted technical advisor to stakeholders and communicating complex technical findings in clear, accessible language.
• Mentoring junior and mid-level Data Scientists through code reviews, pairing and knowledge sharing.
• Contributing to the team's technical roadmap, reusable components and engineering standards.

Your Profile :

• MSc or PhD in Data Science, Computer Science, Statistics, Mathematics, Life Sciences or another relevant quantitative discipline, or equivalent professional experience.
• 5+ years of hands-on experience delivering Data Science or Machine Learning solutions, including experience taking at least one solution into production.
• Strong Python and SQL skills, with experience using libraries and frameworks such as pandas, scikit-learn, PyTorch or Hugging Face.
• Practical experience working with large language models, prompt engineering, embeddings, vector search and RAG architectures.
• Strong grounding in statistics, experimental design and model evaluation.
• Experience working with cloud platforms, preferably Microsoft Azure, and modern MLOps technologies such as MLflow, Docker, CI/CD and orchestration tools including Airflow.
• Excellent communication and stakeholder management skills, with the ability to influence both technical and non-technical audiences.
• Experience within pharma, CRO, healthcare or another regulated industry would be advantageous.
• Familiarity with clinical trial data and standards, such as CDISC, clinical study protocols, site data and investigator data, would be beneficial.
• Experience with Microsoft Fabric, Azure OpenAI/AI Foundry, AKS or knowledge graph technologies would be advantageous.
• Knowledge of causal inference, network analysis or optimisation methods would be beneficial.
• A track record of publications, open-source contributions or patents would be an advantage.

Rewards & Benefits

• Competitive base salary and performance related incentives
• Health and wellbeing programmes including medical, dental, and vision coverage where applicable
• Retirement and pension plans
• Life assurance and disability coverage
• Employee assistance programmes and wellbeing resources
• Learning and development opportunities through structured training and career pathways