What you’ll do
- Prepare, clean and transform data, and engineer features for modelling.
- Explore data to identify patterns and guide model development.
- Build, validate and deploy machine learning models.
- Monitor model performance, investigate drift and retrain models when needed.
- Troubleshoot deployed solutions and maintain reliable pipelines.
- Document models, pipelines and processes so others can understand and maintain them.
- Create dashboards and reporting tools that help business teams use your finding
Requirements
What you’ll need
- A degree or honours qualification in Data Science.
- At least 5 years’ experience in insurance or financial services.
- At least 5 years of hands-on machine learning experience, covering data preparation through to deployment.
- Proven experience with Python or R, and SQL/Snowflake.
- Experience in claims modelling and survival analysis.
- A strong foundation in statistical modelling and time series forecasting.
Experience that would be an advantage
- Short-term insurance experience, exposure to machine learning platforms, and proficiency in BI tools such as Power BI, Qlik Sense or Tableau.