Data Scientist (Lead Specialist) - AI

Roles & Responsibilities

We are expanding our strong data science team and are seeking a talented and driven practitioner with applied experience in leveraging advanced cloud AI services, Retrieval Augmented Generation (RAG) architectures, and robust MLOps practices to develop transformative AI applications. If you are passionate about creating solutions that have a direct and significant real-world impact on healthcare, this opportunity is for you.

We are looking for an individual with a deep passion for deconstructing complex challenges and a talent for creative, resourceful problem-solving. You should possess a strong intellectual curiosity regarding clinical and business needs and demonstrate a proven ability to effectively engage with diverse stakeholders to understand multifaceted problems and collaboratively develop impactful AI-driven solutions thoroughly.

Critical Work Functions and Key Tasks

Data Science & AI for Healthcare

• Analyse diverse, complex healthcare datasets to identify patterns and extract meaningful insights.
• Synthesise findings into actionable recommendations and define opportunities for AI-driven solutions.
• Design, develop, implement, and validate a range of machine learning and AI models—including but not limited to predictive modelling, classification, clustering, natural language processing, and, where applicable, computer vision techniques—to address specific healthcare challenges and improve patient outcomes or operational efficiencies.
• Conduct rigorous validation and testing of AI models to ensure they meet clinical efficacy and regulatory standards.
• Stay updated on the latest developments in artificial intelligence, machine learning, and data science techniques and their applications in the rapidly changing healthcare technology landscape. This ensures that proposed solutions remain relevant, innovative, and effective
• Effectively communicate data-driven insights, analytical results, and model capabilities to diverse stakeholders (both technical and non-technical) through clear presentations, visualisations, and documentation; contribute to disseminating knowledge via research papers or conference presentations when appropriate.

Generative AI Application Development (RAG & Agentic Systems)

CI / CD, MLOps & Backend Engineering

Collaborative work

Requirements

Tell employers what skills you have

TensorFlow

Machine Learning

Azure

Pipelines

Natural Language Processing

Healthcare

Artificial Intelligence

Software Engineering

Computer Vision

PyTorch

Python

Google Cloud

Data Science

Decision Making

Databases

FastAPI