Role Overview
We are seeking an experienced Data Scientist Lead to drive the development and delivery of advanced analytical solutions, with a particular focus on decision engines, Next Best Action (NBA), propensity modelling and predictive analytics.
The role will suit a commercially minded Data Science leader with strong traditional machine learning expertise and the ability to translate complex analytical outputs into actionable business strategies. You will lead the development of predictive models that support customer decisioning, personalisation, customer engagement and business optimisation.
A key component of the position is the ability to work across cross-functional teams, influence senior stakeholders and navigate complex project environments to ensure data science initiatives deliver measurable business outcomes.
Key Responsibilities
- Lead the design, development and implementation of decision engines and Next Best Action capabilities.
- Develop and optimise propensity models, predictive models and customer segmentation solutions using traditional machine learning techniques.
- Translate business objectives into analytical solutions that support customer targeting, engagement, retention and conversion.
- Drive the development of predictive models that inform real-time and near-real-time business decision-making.
- Work closely with business stakeholders to identify opportunities where data science can improve commercial and operational outcomes.
- Lead and coordinate cross-functional delivery teams across Data Science, Data Engineering, Technology, Product and Business functions.
- Communicate complex analytical concepts and model outputs to senior stakeholders, translating insights into clear business recommendations.
- Manage competing priorities, dependencies, delivery milestones and project risks across multiple initiatives.
- Influence decision-making across business and technology teams, ensuring alignment between analytical solutions and broader organisational objectives.
- Establish best practices around model performance, validation, monitoring and continuous improvement.
- Extensive experience in Data Science, Predictive Analytics and Machine Learning.
- Strong experience developing propensity models, Next Best Action solutions and decision engines.
- Solid understanding of traditional machine learning techniques, including:
- Logistic and linear regression
- Decision trees, Random Forest and Gradient Boosting
- Classification and regression modelling
- Customer segmentation and behavioural modelling
- Predictive scoring and propensity modelling
- Strong Python and SQL skills, with experience using relevant data science and machine learning libraries.
- Experience translating analytical models into practical business decisioning solutions.
- Understanding of customer lifecycle management, personalisation and customer engagement strategies.
- Experience leading or mentoring Data Scientists and working with Data Engineering teams to operationalise models.
- Exceptional stakeholder engagement, communication and relationship management skills.
- Demonstrated ability to engage senior business and technology stakeholders.
- Experience navigating complex cross-functional environments and influencing decisions without direct authority.
- Strong understanding of broader project delivery, including planning, dependencies, governance, risks and stakeholder alignment.
- Ability to bring together business, technology, product and analytical teams to drive outcomes.
- Commercially focused, with the ability to connect data science initiatives to measurable business value.
