You’ll bring strong expertise in data visualisation tools, particularly Python, along with experience in MLOps and the ability to translate complex insights into compelling stories. You’ll work across a wide variety of high impact projects within MFE, including our London Marathon initiative, where we’re using machine learning to identify the supporters most likely to generate the greatest income. You’ll also support our Legacies team, which contributes a third of CRUK’s overall income, by developing forecasting models and analytical tools that help them plan confidently and maximise long‑term value.
What will I be doing?
* 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, e.g. 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.
Qualifications
* 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.
Our organisation values
* Bold: Act with ambition, courage and determination.
* Credible: Act with rigour and professionalism.
What will I gain?
We create a working environment that supports your wellbeing and provide a generous benefits package, a wide range of career and personal development opportunities and high‑quality tools. Our policies and processes enable you to improve your work‑life balance, take positive steps in your career and achieve your personal wellbeing goals.
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