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Head: Nonlife Analytics

2 weeks ago

Sandton, South Africa Guardrisk Full time

**Introduction**

Structuring and Solutions team forms the key point of contact between the different segments and the technical support areas, focusing on client service and client solution development. The area works closely with the Marketing teams in the structuring of new deals, providing analytical insights to our clients and business while also providing technical support in the form of pricing, product development and the capital modelling of new business prospects.

**Role Purpose**

The Non-Life Analytics team looks after analytics across the Guardrisk Non-Life business and provides insight to the business that supports decision making and provides analytical insights to clients. The team also works closely with the Pricing and Structuring team in providing insights on products and developing pricing models. The Non-Life Analytics team will also be required to assist the business with ad-hoc requests, where the skillset of the team is required, from time-to-time.

**Requirements**:

- Bachelor's degree in Actuarial Science, Mathematics, Statistics, Computer Science, Data Mining, Data Analytics, Computer Science, Informatics, or equivalent
- At least 7 years’ experience within an insurance environment
- Extensive knowledge of at least one programming language (e.g., Python), business analytics software and statistical packages (e.g., R)

**Duties & Responsibilities**
- Head up the Non-Life Analytics team
- Identify and develop Predictive and Prescriptive Models to enable better decision making of business.
- Identify, understand and interpret data structures across various databases within the business to facilitate data analysis and continuous monitoring activities.
- Delve for insights in data and processes to help improve the business.
- Contribute to the development of differentiated; superior solutions that meet stakeholder and business requirements through analysis; business requirements gathering and designs validation.
- Participate and/or lead discovery processes with business stakeholders to identify problems and opportunities that may be addressed with statistical modelling or machine learning.
- Collaborate with business to define approach to resolution of key business problems or development of new business strategies.
- Contribute to the business by highlighting possible opportunities for process improvement and business value creation.
- Make strategic recommendations on data collection and experimental design incorporating business requirements and knowledge of best practices.
- Identify and train suitable models/algorithms to discover patterns and make predictions.
- Extend existing code and develop custom code to implement statistical models, machine learning algorithms and data mining techniques for large datasets in a computationally efficient manner.
- Compare model performance, select the best algorithm for the job and be able to motivate this choice in a non-technical manner.
- Interpret results and translate findings into clear and actionable insights that can be easily validated with the project sponsor.
- Communicate findings to business with various skill levels and in various roles, presenting trends, correlations and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights
- Assist business users in the use of the models and interpretation of model output.
- Assist with monitoring and reporting on model accuracy after it has been embedded in operations.

**Competencies**
- Analytical thinking
- Numeric skills
- Attention to detail
- Innovative
- Collaborative
- Excellent written and verbal communication skills
- Organised person with interpersonal skills
- Comfortable with different insurance pricing techniques
- Quick learner and self-starter
- Ability to adapt to change
- Thinking laterally to solve complex problems
- Ability to work accurately under pressure and meet deadlines