Lead Data Scientist

SUMMARY:
A leading organisation is seeking an experienced and innovative Lead Data Scientist to drive the development and delivery of advanced analytics, machine learning solutions, and data-driven products that create measurable business value. This role offers the opportunity to lead complex data science initiatives, influence strategic decision-making, and mentor a high-performing team of data professionals within a dynamic and fast-paced environment.

POSITION INFO:
The successful candidate will combine strong technical expertise with leadership capabilities, leveraging large and complex datasets to solve critical business challenges. You will work closely with business stakeholders, data engineers, and software development teams to design, develop, and deploy scalable analytical solutions while championing best practices in data science and advanced analytics.

Key Responsibilities:

• Lead the delivery and execution of enterprise-wide data science projects and advanced analytical solutions.
• Partner with business stakeholders to identify opportunities and translate complex business requirements into data-driven solutions.
• Design, develop, and implement machine learning, predictive analytics, statistical, and AI-driven models.
• Collaborate with technology and engineering teams to develop scalable, production-ready analytical products.
• Drive project planning, prioritisation, and execution while balancing technical feasibility with business objectives.
• Oversee data preparation, feature engineering, model development, validation, deployment, and ongoing monitoring.
• Establish and maintain data quality standards and governance practices.
• Present analytical findings and strategic recommendations to senior leadership through compelling data storytelling and visualisation.
• Evaluate and implement emerging technologies, tools, and methodologies to enhance analytical capabilities.
• Provide technical leadership, coaching, and mentorship to Data Scientists and analytical teams.
• Promote innovation, collaboration, and continuous improvement across the broader data function.
• Contribute to the organisation's long-term data and analytics strategy.

• Bachelor's Degree in Data Science, Computer Science, Mathematics, Statistics, Information Systems, Information Technology, or a related quantitative field.
• Postgraduate qualification (Honours or Master's Degree preferred)

• Proven experience applying machine learning, predictive modelling, deep learning, statistical analysis, and data mining techniques to solve business challenges.
• Advanced proficiency in Python, SQL, and modern data science tools and frameworks.
• Experience leading projects and mentoring junior team members.
• Exposure to Agile, Lean, or Design Thinking methodologies.
• Strong Microsoft Office Suite skills, including advanced Excel.
• Experience working with large-scale datasets in a commercial, technology, financial services, retail, or enterprise environment is advantageous.

• Exceptional analytical, problem-solving, and critical-thinking skills.
• Ability to interpret complex data and translate insights into meaningful business outcomes.
• Strong leadership and mentoring capabilities.
• Excellent communication and stakeholder engagement skills.
• Ability to present technical concepts clearly to both technical and non-technical audiences.
• Highly organised with strong attention to detail and quality.
• Commercially minded with a strong understanding of business drivers and objectives.
• Adaptable, innovative, and passionate about emerging technologies and data-driven decision-making.
• Proven ability to manage multiple priorities in a fast-paced environment.
• Collaborative team player with strong relationship-building skills.

• Actuarial: Life, Short-Term, Health, Pensions, and Quantitative
• Data & Analytics: Data Scientists, Data Analysts (Python, R, SQL, Machine Learning)
• Risk: Credit Risk, Market Risk, Model Risk, and Operational Risk Analysts
• Pricing: Specialists in Insurance and Financial Products
• AI & Machine Learning: ML Ops, NLP, Predictive Modelling Data Scientists
• Quantitative: Experts across Banking, Insurance, and FinTech