Data Scientist - Machine Learning Models

Key Responsibilities

• Lead the application of advanced analytics and machine learning across Marketing to drive strategic, data-informed decisions.
• Design, build, and deploy predictive models and trigger-based audiences for use in Marketing communications across multiple media channels.
• Enhance and manage feature engineering processes and feature store development for Marketing use cases.
• Integrate digital analytics (e.g., Adobe Analytics) into data science models and use cases.
• Deliver outcomes aligned with the AI/ML roadmap and architecture capabilities.
• Continuously identify, promote, and embed new advanced analytics techniques within the team and across the Marketing function.
• Present complex analytical findings in a clear and actionable manner using visualisation tools and insight presentations tailored to senior stakeholders.
• Develop innovative analytic approaches to uncover unmet customer needs and improve financial wellbeing.
• Champion standardisation and reusability of code, features, and solutions to improve time to insight.
  

Key Performance Indicators (KPIs)

• Timely and high-quality delivery of data science solutions aligned to business goals.
• Recognition as a key contributor to innovation and the development of Marketing analytics capabilities.
• Measurable improvements in insight delivery timelines through standardized and reusable frameworks.
• Strong stakeholder relationships; known as a trusted advisor within the business.
  

Essential Capabilities

• Passion for analytics and data science, with awareness of the latest industry trends.
• Proven ability to solve business problems using data and analytical techniques.
• Strong strategic and customer-centric mindset.
• Ability to communicate complex concepts clearly to non-technical stakeholders.
• Strong problem-solving, documentation, and analytical thinking skills.
• Self-management and accountability for personal tasks and project deliverables.
• Collaboration and influencing skills across cross-functional teams.
  

Essential Experience

• 10+ years of experience in data science, analytics, or related fields.
• Expertise in building, deploying, and operationalising machine learning models.
• Proficiency in SQL, Python, PySpark, and Spark ML.
• Hands-on experience with cloud platforms such as AWS (preferred), Azure, or GCP.
• Skilled in using GitHub for version control and collaboration.
• Strong experience in working with both structured and unstructured datasets.
• Familiarity with Auto ML platforms such as Data Robot or H2O AI.
• Deep understanding of customer and digital data, and their use in marketing and communications.
• Experience with agile delivery methodologies and collaboration tools.
  

Desirable Experience

• Leadership in the use of AI/ML and analytics to guide Marketing strategy.
• Input into development of AI roadmaps and alignment with architecture/platform capabilities.
• Ownership of continuous improvement in analytics tools, techniques, and adoption.
• Skilled in visualising data using tools such as Tableau, Power BI, or similar.
• Experience in developing innovative solutions that address both met and unmet customer needs.
  

Qualification Requirements

• Bachelor's or postgraduate degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or related disciplines.
• Key Stakeholder Groups
• Principal Data Scientist
• Product Owners across the Marketing domain