Head of Data Science

Job Description

Overview

Stalis has built its reputation on delivering high-quality healthcare data migrations, integrations, and archiving solutions. The Head of Data Science is a newly created role responsible for furthering our mission into data intelligence and advanced analytics.

This is a founding role in the data science function. The postholder will work directly with the CEO and COO to define the roadmap, build the team, and deliver tangible outcomes for both internal operations and external clients.

Applications in the UK, USA and Republic of Ireland will be considered

Key Responsibilities

• Identify and prioritise methods to optimise internal processes — including migration workflows, schema mapping, QA, and project delivery.

• Build and deploy tech-enabled tooling to improve delivery accuracy and efficiency.

• Establish a culture of data-driven decision-making internally — supporting leadership with analytics, reporting, and operational insight.

• Develop and commercialise new capabilities within the data intelligence space.

• Work with clients and clinical stakeholders to understand unmet needs and translate them into AI/ML solutions.

• Design, train, and productise machine learning models for healthcare use cases.

• Build and maintain robust MLOps practices: versioning, monitoring, retraining pipelines, and deployment infrastructure.

• Own and drive Stalis’s company-wide data science strategy — defining principles, priorities, and governance for adoption across the business.

• Serve as the internal authority on technology developments — advising the leadership team on emerging technologies, competitive trends, and strategic risks and opportunities.

• Define the data science team structure needed to deliver the roadmap.

• Establish engineering standards, tooling choices, and ways of working for the data science function.

Requirements

Essential

• Hands-on experience in applied machine learning and data science, ideally within healthcare or a similarly regulated sector.

• Strong Python development skills and experience with ML frameworks (e.g. scikit-learn, PyTorch, HuggingFace Transformers).

• Demonstrated ability to take AI/ML projects from idea through to deployed, production-quality systems.

• Experience working with databases and structured data at scale — including SQL, schema design, and ETL/data engineering concepts.

• Comfortable operating as both a technical individual contributor and a strategic thinker — able to write code and present to leadership.

• Strong communication skills: able to explain complex technical concepts to non-technical audiences.

Desirable

• Experience with NLP applied to clinical text (e.g. clinical notes, discharge summaries, lab results).

• Familiarity with healthcare data standards — HL7, FHIR, SNOMED CT, NHS data models.

• Experience with clinical decision support systems or patient safety analytics.

• Knowledge of PHI compliance, DSPT, and UK data governance requirements in healthcare settings.