Senior Data Scientist at Hollard Insurance

Job Purpose

• Lead the delivery of advanced analytics and data science solutions that drive material business value across the Hollard Life Solutions by transforming decision-making through insight-led, data-driven approaches. The role is accountable for translating complex business problems into analytical solutions, influencing strategic decisions, embedding analytics into core processes, and uplifting data science capability across Life Solutions.

Key Performance Area’s

Advanced analytics and modelling (technical)

• Model complex business problems using advanced statistical, machine learning and optimisation techniques
• Develop predictive, prescriptive and diagnostic models to support pricing, underwriting, claims, fraud, sales and marketing decisions
• Evaluate, validate and refine models to ensure robustness, interpretability and performance

Insight Generation and Value Realisation (technical)

• Translate analytical outputs into clear, actionable business insights and recommendations
• Quantify financial and operational impact of analytics initiatives and track value realisation
• Drive a test-and-learn agenda by structuring experiments, analysing results and embedding learnings

Solution Development and Deployment (technical)

• Design and implement scalable analytical tools, dashboards and data products
• Partner with data engineering and BI teams to ensure production-ready solutions
• Ensure models are operationalised, monitored and maintained over their lifecycle

Data governance and Risk management (technical)

• Ensure adherence to data governance, model risk and ethical AI principles
• Document models, assumptions and limitations to support audit and regulatory requirements
• Promote responsible use of data in line with organisational standards

Stakeholder Engagement and Influence (behavioural)

• Partner with senior business stakeholders to shape analytics roadmaps and priorities
• Influence decision-making through evidence-based insights and trusted advisory support
• Communicate complex analytical concepts clearly to non-technical audiences

Capability Building and Leadership (behavioural)

• Coach and mentor data scientists and analysts to uplift technical and commercial capability
• Contribute to analytics standards, frameworks and best practices
• Support team development and knowledge sharing across the analytics community

Required Knowledge and Experience    
Technical Competencies

• Advanced statistical analysis and machine learning
• Data modelling and feature engineering
• SQL, Python/R and analytical toolsets
• Experiment design and causal inference
• Data governance and model risk management

Key Measurements of Outputs

• Business value delivered through analytics initiatives
• Quality, accuracy and performance of models and insights produced
• Adoption of analytics solutions within business processes
• Effectiveness of stakeholder engagement and decision support
• Contribution to data science capability uplift and maturity

Educational Requirements    
Qualifications

Minimum qualifications

• BSc or MSc in mathematics, statistics, computer science, engineering, actuarial science or similar quantitative discipline

Desirable qualifications

• Postgraduate qualification in data science, analytics or machine learning
• Professional certification in data science, analytics or cloud platforms

Deadline:14th April,2026