
Dotsure Statistical Modeller (George, Western Cape)
- George, Western Cape
- Permanent
- Full-time
- Develop and enhance telematics-based scoring models to evaluate driver behaviour and risk profiles.
- Conduct deep statistical analysis on large insurance and telematics datasets to identify trends and risk signals.
- Build predictive models for pricing, claims forecasting, and behavioural insights.
- Collaborate with cross-functional teams to ensure model outputs drive effective product and business strategies.
- Improve driver risk indicators (e.g., claim probabilities, first notice of loss accuracy, behavioural flags).
- Present complex analyses and modelling results in a clear and compelling way to technical and non-technical stakeholders.
- Bachelor’s or Honours degree in Actuarial Science, Statistics, Data Science, or related quantitative field.
- 2–4 years of experience in statistical modelling, actuarial analytics, or insurance data.
- Previous work in motor insurance or telematics-driven roles is a strong advantage.
- Advanced knowledge of statistical modelling techniques (e.g., GLMs, correlation studies, distribution analysis).
- Proficiency in Excel, R, SAS, or similar actuarial/statistical tools.
- Experience working with SQL and large-scale datasets.
- Python skills are a bonus but not required.
- Strong analytical thinker with a solid grasp of behavioural data and risk modelling.
- Excellent communicator—able to explain complex insights with clarity and precision.
- Self-driven, collaborative, and thrives in a fast-paced, high-impact environment.
- A supportive, innovation-focused team culture
- Opportunities to grow into strategic and technical leadership roles
- Exposure to real-time telematics and AI-driven initiatives
- A space to make an impact, your work will matter
Join us at Dotsure and build models that power smarter insurance.Apply today and let’s reimagine telematics together.The position will be filled in line with Dotsure's culture, values, and Employment Equity policy. Preference will be given to candidates from under-represented designated groups