Key Responsibility’s 

• Solve business and technical problems related to customer acquisition, retention, and experience with robust use of rigorous scientific methodologies and creative use of algorithms using AI, machine learning and predictive modelling techniques on a cloud platform
• Develop Develop and deploy customer-focused ML solutions frameworks for customer analytics best practices, and work closely with the Data Science Chapter Lead and data platform team to automate frameworks for scalability to the wider business
• Produce creative data visualisations and intuitive graphics to present complex customer analytics findings
• Work closely with data engineers, platform engineers, and fellow data scientists in an agile environment to deliver work that adheres to the processes and quality standards set by the team

What you will ideally bring: 

• Strong understanding of the end-to-end ML lifecycle, including MLOps for model deployment, monitoring, and maintenance of customer-facing models
• Tertiary degree (or equivalent experience) in a highly analytical discipline (e.g. data science, statistics, mathematics, computer science, economics, engineering
• Minimum three years' experience in customer analytics, data science, or related analytical roles in competitive consumer retail markets such as energy, financial services, insurance, telecommunications, travel, hospitality or airlines
• Strong knowledge of advanced analytical and statistical techniques including modelling, ML and AI, with specific application to customer analytics use cases
• Excellent communication and presentation skills with the ability to clearly explain key customer insights to a non-technical audience and the ability to influence stakeholders
• Experience in Python, SQL, and familiarity with cloud data platforms (Snowflake, AWS, Azure, or GCP)
• Proficiency with data science libraries and frameworks (pandas, scikit-learn, TensorFlow/PyTorch, MLflow, or similar)
• Understanding of customer analytics concepts including segmentation, churn prediction, customer lifetime value, attribution modelling, and journey analytics
• Excellent problem-solving skills with the ability to think creatively and 'outside of the box' when approaching customer challenges
• Experience with data visualisation tools, such as Power BI, Tableau, or similar, is preferred
• Strong stakeholder management and influencing skills, particularly with customer-facing business teams
• Experience with agile development methodologies and cross-functional collaboration