Key functional responsibilities include: 

• Lead the design and implementation of complex business and technical solutions using advanced AI, deep learning, and predictive modelling techniques on cloud platforms, with demonstrated ability to work across multiple business domains simultaneously
• Drive innovation through research and implementation of cutting-edge advanced analytics opportunities in areas of predictive modelling, optimisation, deep learning, reinforcement learning, NLP, computer vision, and other emerging ML techniques to identify and deliver transformational business solutions
• Establish and champion frameworks for data science best practices, including model development standards, MLOps processes, and technical governance, working closely with the Data Science Chapter Lead to automate and scale these frameworks across the organisation
• Expert-level understanding of the end-to-end ML lifecycle, with hands-on leadership in MLOps for model deployment, monitoring, maintenance, and continuous improvement in production environments
• Produce sophisticated data visualisations and compelling narratives to communicate complex analytics findings to senior leadership and drive strategic decision-making
• Provide technical leadership and mentorship to junior data scientists and analysts in an agile environment, ensuring delivery of work that adheres to the highest standards of quality and rigour
• Act as a trusted strategic adviser to senior stakeholders and leadership teams, translating business challenges into analytical solutions and building organisational capability in data science

Successful applications will demonstrate:

• Tertiary degree (or equivalent experience) in a highly analytical discipline (e.g. data science, statistics, mathematics, physics, computer science, engineering)
• Minimum 5-7 years' experience in data science, machine learning, or advanced analytics roles with demonstrated progression in seniority and complexity
• Significant experience in competitive consumer retail markets such as airlines, travel, hospitality, financial services, insurance, telecommunications, or e-commerce
• Proven track record of leading complex analytical projects from conception to production deployment with measurable business impact
• Experience working with senior stakeholders and translating business strategy into analytical solutions
• Deep experience with end-to-end ML lifecycle including model development, deployment, monitoring, and maintenance in production environments
• Track record of innovation and problem-solving in complex, data-rich business environments
• Extensive experience with modern data platforms (Snowflake, Databricks, AWS/Azure/GCP) and ability to architect scalable data science solutions
• Expert-level knowledge of ML frameworks and libraries (scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, etc.) with understanding of when to apply different approaches
• Strong understanding of MLOps practices including containerisation (Docker), orchestration (Airflow, Kubeflow), model serving, and monitoring
• Advanced skills in data visualisation and storytelling, using tools such as Power BI, Tableau, or custom visualisation libraries