Data Scientist

Full Stack Data Scientist / ML Engineer

Freelance - contract opportunity

We are looking for a Full Stack Data Scientist / ML Engineer to support a global Medical Device business on their AI journey.

You will play a pivotal role in advancing our Advanced Analytics capabilities, acting as both a technical leader and a trusted partner to business stakeholders across the organisation.

This is a high-impact position for someone who takes genuine ownership, leads by example, and is passionate about embedding data science best practices at scale.

Responsibitlies

• Partner with stakeholders across the organisation to understand business objectives and co-design data-driven solutions

• Work closely with Analytics Product Owners and the Cloud/Engineering team to deliver Data Science and ML workstreams on time, within budget, and to quality standards

• Lead and facilitate ideation and scoping sessions with business stakeholders to define the data needed to address specific challenges

• Champion best practices, standards, and methodologies across your Advanced Analytics capability area, ensuring consistently high-quality data science output

• Articulate the value of your domain (e.g., AI/ML) to the broader organisation, shaping decision-making and becoming a go-to advisor for key business stakeholders

• Evaluate and recommend new technologies and ML techniques that improve efficiency and accelerate delivery

• Foster a culture of continuous learning, knowledge sharing, and professional growth within the team

• Own the end-to-end documentation, demos, and presentations required to communicate and validate your solutions

Requirements:

• Azure AI Services — AI Foundry, OpenAI, AI Search, Document Intelligence

• Container Apps, Container App Environments, and Container Registries

• Application Gateway, Key Vault, Managed Identities

• Storage Accounts and Virtual Networks

• Python — production-grade code, with strong experience in LangChain, Pydantic, and FastAPI

• ETL development, including parallel computing approaches

• Generative AI — Prompt Engineering, Retrieval-Augmented Generation (RAG), and GenAI application architecture

• Terraform (Infrastructure as Code)

• Docker

• Code versioning via Azure Repos

• CI/CD pipeline development using Azure Pipelines

• Linting, unit testing, and adherence to software development best practices

• Industry experience within a highly regulated environment, MedTech, Life Sciences, Food

Nice to Have

• React development experience, including TypeScript, REST/GraphQL, state management, UI/UX principles, HTML/CSS, and caching strategies