Job Description
The Pricing & Portfolio Insights Data Analyst is an integral role within our insurance company, responsible for leveraging their expertise in data analytics to assist with data processing and transformation, pricing analysis, providing insights on the portfolio, and producing regular monitoring reports to help track vital KPIs. This position requires a strong background in data analysis & statistical modelling. Knowledge and experience in machine learning algorithms would be preferred.
This role is responsible for assisting the conduction of robust quantitative and statistical analysis of our insurance product offerings and portfolio. The role involves helping analyse complex datasets to identify trends, patterns and insights that serve to improve product performance, optimize portfolio management, and inform strategic decision-making.
In this pivotal role, the Pricing & Portfolio Insights Data Analyst will collaborate closely with various stakeholders including Underwriting, Actuarial, Risk Management, and the Executive Team in assisting evidence-based decisions, promoting profitability, and enabling efficient portfolio management.
Key Accountabilities & Responsibilities
- Analyse historical insurance data to identify patterns, trends, and abnormalities of factors in the various portfolios.
- Work closely with data engineering teams to optimize data storage, retrieval, and processing, and ensuring efficient handling of datasets.
- Create clear and effective data visualizations and communicate findings to stakeholders in a clear and concise manner, providing insights for business decision-making.
- Collaborate with cross-functional teams to understand business objectives and identify areas where data-driven solutions can drive revenue, growth, renewals, and/or claims efficiency.
- Stay up to date with the latest advancements in data related subjects and actively seek opportunities to apply new techniques and tools to enhance business opportunities.
- Develop and monitor performance metrics for data analysis processes to identify bottlenecks and areas for improvement.
Skills & Experience
- Bachelor’s degree (or equivalent) in Data Science, Actuarial Science, Statistics, Mathematics, Economics, or Computer science
- 2+ years of related practical experience.
- Strong programming skills in languages like SQL, R or Python for data manipulation and analysis.
- Experience with data visualization tools such as Qlikview/QlikSense, Tableau or Power BI.
- Excellent communication skills to effectively present complex findings to both technical and non-technical stakeholders.
- Preferred:
- Solid understanding of insurance industry dynamics and business processes.
- Proficiency in machine learning techniques such as regression, clustering, and recommendation systems.
