Data Scientist

Data Scientist

Up to £90,000pa

Remote Based

About the Role

We are seeking a hands-on Data Scientist to join our team as our first dedicated data science hire. This is a unique opportunity to build our AI and data capability from the ground up, working directly with leadership to establish data-driven decision making across the organization. The successful candidate will have the potential to grow and lead a data science team as we scale.

Key Responsibilities

• Design and implement data science solutions to drive business insights and decision-making
• Build and deploy machine learning models to solve real business problems
• Develop and maintain data pipelines and analytics infrastructure on Azure
• Collaborate with cross-functional teams to identify opportunities for data-driven improvements
• Establish best practices for data science workflows, model deployment, and monitoring
• Leverage AI tools to enhance productivity and accelerate project delivery
• Create dashboards, reports, and visualizations to communicate findings to stakeholders

Essential Requirements

Technical Skills:

• Proficiency in Python or R for data analysis and machine learning
• Strong SQL skills for data extraction, transformation, and analysis
• Experience with Azure cloud platform and services
• Hands-on experience with AI productivity tools (e.g., GitHub Copilot, ChatGPT, etc.)
• Practical machine learning experience including model development, validation, and deployment
• Experience working with data platforms and infrastructure (any technology stack)

Professional Experience:

• Proven track record of delivering data science projects in a business environment
• Experience translating business requirements into technical solutions
• Strong problem-solving skills with a practical, results-oriented approach
• Excellent communication skills to present findings to both technical and non-technical audiences

Desirable Skills

• Experience with Azure Machine Learning, Azure Data Factory, or other Azure data services
• Knowledge of MLOps practices and tools
• Experience with data visualization tools (Power BI, Tableau, etc.)
• Understanding of statistical analysis and experimental design
• Experience building data science capabilities from scratch