Lead Data Scientist

Position Summary

We are seeking a Lead Data Scientist to provide technical leadership across data science initiatives and deliver reliable, scalable, and impactful analytical solutions. This role is responsible for defining data science strategy, leading complex modelling projects, developing team capability, and partnering with product, technology, commercial, and business stakeholders. The ideal candidate combines strong expertise in statistics, machine learning, and data engineering with proven leadership skills and the ability to translate complex analysis into practical business outcomes.

Key Responsibilities

• Lead, mentor, and develop data scientists and related analytical specialists, promoting a collaborative, inclusive, and high-performing culture

• Define and implement data science strategies, standards, methodologies, and best practices aligned with organisational objectives

• Lead the delivery of data science projects across the full lifecycle, including problem definition, data exploration, feature engineering, modelling, validation, deployment, and monitoring

• Partner with Product Management, Engineering, Data Engineering, Analytics, Operations, and business stakeholders to identify opportunities and define measurable outcomes

• Provide technical leadership on statistical analysis, machine learning, predictive modelling, experimentation, optimisation, and artificial intelligence initiatives

• Translate complex data science concepts and findings into clear recommendations for technical and non-technical stakeholders

• Establish and maintain standards for data quality, model development, validation, reproducibility, documentation, and responsible use of data

• Review analytical approaches, model designs, code, assumptions, and results to ensure accuracy, robustness, and business relevance

• Oversee the development, deployment, and ongoing performance monitoring of machine learning models and data products

• Identify risks relating to bias, privacy, explainability, data protection, model drift, and regulatory compliance, and implement appropriate controls

• Support recruitment, onboarding, performance management, career development, and succession planning for data science team members

• Manage priorities, delivery plans, dependencies, resources, and risks across multiple data science initiatives

• Identify opportunities to improve analytical processes, data availability, modelling techniques, tooling, automation, and team productivity

• Provide regular reporting to senior leadership on project progress, business impact, model performance, team capacity, technical risks, and future requirements

Required Qualifications

• Significant experience in data science, machine learning, statistics, quantitative analysis, or a related technical discipline, including experience leading data science projects or teams

• Proven experience applying statistical and machine learning techniques to solve complex business or operational problems

• Strong understanding of supervised and unsupervised learning, predictive modelling, feature engineering, model evaluation, experimentation, and statistical inference

• Practical experience with Python or R and common data science libraries and frameworks

• Experience working with SQL, relational or non-relational databases, data warehouses, and large or complex datasets

• Experience taking data science models or analytical solutions from development through deployment, monitoring, and ongoing improvement

• Experience managing or mentoring data scientists through coaching, technical review, professional development, and team planning

• Ability to communicate complex technical concepts, analytical findings, and business recommendations clearly to both technical and non-technical stakeholders

• Strong problem-solving, critical thinking, decision-making, organisational, and stakeholder management skills

• Strong understanding of data governance, information security, data protection, model risk, and responsible artificial intelligence principles

• High attention to detail balanced with the ability to take a strategic, organisation-wide view of data science and analytical delivery

Preferred Qualifications

• Experience leading distributed or cross-functional data science and analytics teams

• Experience with deep learning, natural language processing, computer vision, time series forecasting, recommendation systems, or optimisation

• Experience with cloud data and machine learning platforms, including AWS, Microsoft Azure, or Google Cloud

• Experience with MLOps, model governance, feature stores, experiment tracking, model monitoring, and automated machine learning workflows

• Experience working with distributed data processing technologies, data pipelines, APIs, and modern data platforms

• Relevant degree or professional qualification in data science, computer science, statistics, mathematics, engineering, or a related field

• Research experience, published work, patents, or contributions to open-source data science and machine learning projects

• Experience working in an environment with formal information security, data protection, quality, or regulatory requirements