What will you do?

• The purpose of the role is to join a small group of data pioneers to wrangle data, enhance business reporting and build models to enhance decision-making and profitability.
• This is a unique opportunity to work in a dynamic environment and collaborate across analytics teams, while having the freedom to create the data assets that you will model on; with technical data work, reporting and modelling being the core responsibilities of the role.

What will make you successful in this role?

• Data wrangling
• Building data flows from multiple sources in SAS and creating data assets in Hadoop
• Dashboard and Report creation
• Data extracts for adhoc business requests
• Trend analysis and reporting from extracted data
• Assist stakeholders by doing manual extracts from existing dashboards and SQL sources where required
• Look for opportunities to improve existing reports and dashboards
• Collaborate with multiple analytics teams to ensure efficient delivery
• Work closely with actuarial and pricing teams on collaborative insights and modelling projects
• Work with the underwriting team to come up with unique insights that drive underwriting rules and decisions
• Do web scraping and data acquisition from novel data sources for insights and analysis

Qualification and Experience

• Degree in Actuarial Science/Econometrics/Statistics/Computer Science/Data Science or related field.
• 2-3 years of work experience, preferably in the insurance industry
• Advanced SQL skills, including data processing, query optimisation, ability to utilize different SQL dialects (MsSQL, Hadoop SQL, Sybase)
• Experience in R, Python (essential) and SAS (preferred) – SAS and Python are used in the role
• Experience with PowerBi (essential) and Qlik/QlikSense (preferred)
• Advanced Excel skills (Power query, VBA, complex formulas)
• Hands on understanding of insurance concepts and accounting data
• Hands on experience with web scraping, API development and data science application development will be beneficial
• Previous practical experience within insurance pricing, underwriting and claims environments will be beneficial
• Understanding and working experience with machine learning and statistical modelling, especially GLMs, decisions trees and feature engineering

Knowledge and Skills

• Data design
• Problem solving
• Business Knowledge
• Statistical and Data modelling