Role overview
Senior Data Scientist X 2
£ 4 6 ,000 - £ 53 , 000 plus benefits
Reports to: Senior Manager Data Science and Automation
What you'll work on
Lead ML/AI projects with stakeholders across CRUK, working with key stakeholders to document ML/AI objectives and requirements.
Develop data and modelling initiatives, leveraging industry best practice and internal compliance frameworks
Coach data scientists in ML/AI methodologies to enable knowledge growth amongst the team.
Implement models using a robust MLOPs process, from ingestion through modelling to on-going monitoring and performance
Ensure correct experimentation and measurement approach is implemented for all ML/AI initiatives
Deliver LLM capabilities into CRUK, ie . summarisation tools, smart search
Collaborate with other team members to create a culture of high-performance, sharing knowledge in Python, via AWS Sagemaker /Snowpark and other tools
Build, develop and manage relationships and share skills and learning with key stakeholders and networks to ensure the work of the department matches needs and builds capability.
What we're looking for
Related degree in computer science, mathematics, or related STEM field, or equivalent work experience within this field
Demonstrable hands-on skills and experience in technical coding language and data visualisation tools ( e.g.. SQL, Python, Snowflake, PowerBI , Databricks, GA), providing and implementing best practice guidance and standards.
Experience of using statistical analysis to understand and drive value from consumer behaviour, including setting up supervised & unsupervised learning models, covering data cleaning, data analytics, feature creation, model selection, performance metrics & visualisation
Hands-on experience applying MLOps principles (e.g. Snowpark, MLFlow , Github )
Experience in creating and developing high performing experimentation analytical support (test and learn, multivariate tests, ML optimisation, automations).
Experience in a large-scale organisation within a matrixed environment, where essential skills include influencing and managing stakeholders to bring data science to life
Understanding of recommendation systems would be beneficial but isn’t essential