Explore datasets to identify patterns and answer business questions.
Build and test statistical and machine learning models with guidance from the team.
Support model deployment and help monitor performance over time.
Help investigate data issues and troubleshoot model outputs.
Keep clear records of your analysis, code and modelling decisions.
Contribute to dashboards and reports, and explain your findings to business teams.
Requirements
What you'll need
A degree in Data Science or a related quantitative field.
1 - 3 years of relevant experience in data science, analytics or machine learning.
Practical experience using Python or R, and SQL to work with data.
An understanding of statistics, common machine learning methods and model evaluation.
The ability to explain your findings clearly and ask for guidance when needed.
Careful attention to data quality and a willingness to learn from feedback
Experience that would be an advantage
Exposure to insurance or financial services, Snowflake, or BI tools such as Power BI, Qlik Sense or Tableau would be useful. Familiarity with claims modelling, survival analysis, time series forecasting or model deployment would also be an advantage. These are not essential requirements.