We are seeking a talented Data Science Actuarial Analyst to join a leading insurer in Manchester. The team is dedicated to delivering cutting-edge analytical insights, ensuring data-driven decision-making that supports the company's strategic goals.
The Data Science Actuarial Analyst will be responsible for utilising advanced data science and actuarial techniques to analyse complex data sets, support risk management, and contribute to the development of pricing models and financial forecasts. This role offers the opportunity to work alongside senior actuaries and data scientists in a collaborative environment focused on innovation and continuous learning.
Key Responsibilities
1. Develop, maintain, and optimise predictive models for pricing, reserving, and risk management.
2. Perform complex data analysis to support actuarial reporting and decision-making.
3. Work closely with the actuarial team to interpret results, explain trends, and provide actionable insights.
4. Utilise statistical techniques and machine learning algorithms to enhance actuarial processes and improve prediction accuracy.
5. Assist in the development of data-driven strategies to manage financial risk across different products and portfolios.
6. Communicate findings effectively to both technical and non-technical stakeholders, including senior management.
7. Contribute to the automation and streamlining of actuarial processes, ensuring efficiency and consistency.
8. Collaborate with data engineers and software developers to implement data pipelines and systems for enhanced model deployment.
9. Stay up-to-date with industry trends, emerging technologies, and best practices in actuarial data science.
Essential Skills & Qualifications
Experience:
* At least 2 years of experience in an actuarial, data science, or similar analytical role, within the non-life insurance sector.
Technical Skills:
* Strong proficiency in programming languages such as Python, R, or SQL.
* Experience with statistical analysis, machine learning algorithms, and data manipulation techniques.
* Familiarity with actuarial methods and tools (e.g., pricing, reserving, financial forecasting).
* Knowledge of data visualization techniques and tools (e.g., Tableau, Power BI, matplotlib).
* Experience with cloud-based platforms (AWS, Azure) and big data tools (Hadoop, Spark) is a plus.
Educational Background:
* A degree in Actuarial Science, Mathematics, Statistics, Computer Science, Data Science, or a related field.
* Progression towards actuarial exams.
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