Job Description

Introduction

The successful candidate will work closely with internal stakeholders across technical and business teams to identify opportunities, solve complex problems, and translate data into practical insights. Responsibilities include building automated reports and dashboards, developing scalable analytics solutions, and driving data-informed decision-making across key areas of the business.

This role requires strong proficiency in Python, SQL, and Power BI, along with the ability to operate independently in a dynamic and often ambiguous environment. A curious mindset, strong communication skills, and the ability to "own the problem" from end to end are essential to success.

Disclaimer

As an applicant, please verify the legitimacy of this job advert on our company career page.

Role Purpose

The primary purpose of this role is to deliver actionable insights, robust analytics, and data-driven support across Guardrisk Life's portfolio. This is a mid-to-senior level Data Scientist role within the Data Analytics Life team, focused on unlocking business value through intelligent use of data.

Requirements

Bachelor's degree in sciences or engineering with a strong focus on computer science, statistics, mathematics and/or actuarial sciences
Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Actuarial Science, or a related quantitative field
Postgraduate qualification in a relevant field advantageous
Proficiency in Python and SQL is essential
Beneficial: familiarity with DAX, Power BI, or VBA for reporting and automation tasks
Solid understanding of data infrastructure, version control (e.g., Git), and software development principles3-5 years of experience in data science, data analytics, or data engineering within a commercial or financial services environment
Experience working with large datasets in SQL and Python, with the ability to extract, clean, and analyse data efficiently
Experience with business intelligence tools, particularly Power BI, including data modelling and DAX measures
Experience validating data and outputs across multiple sources/systems (UAT or product testing experience advantageous)
Familiarity with insurance and/or actuarial data preferred

Duties & Responsibilities

Predictive modelling capability
Familiarity with machine learning principles, with the ability to implement models when appropriate
Critical analytical thinking and strong attention to detail
Creative, out-of-the-box problem solving
Ability to load, clean, and transform data from various formats (files, databases, APIs)
Validate and enrich data using external/internal sources
Feature engineering capabilities
Ensure data version control and integrity for audit purposes
Use BI tools (e.g., Power BI) to generate actionable insights
Build automated, reusable Power BI reports for stakeholders across business units
Present insights in a format that is both technically accurate and business-ready
Understand operational insurance environments and the data flows within them
Analyse and document business processes to unlock value from data
Assist with user acceptance testing (UAT) for product implementations, ensuring pricing logic and system configuration align with specifications
Conduct root cause analysis when test results deviate from expected outcomes
Ability to present complex findings clearly to technical and non-technical stakeholders
Proactively engage with business users to refine requirements and validate results
Intellectual curiosity and drive to continuously learn new tools, frameworks, and domain knowledge
Ability to understand and break down insurance processes and translate them into business and data requirements
Identify opportunities for process automation
Understanding of insurance and product lifecycles is advantageous; willingness to learn sector-specific concepts is essential

Competencies

Data Mining
Stakeholder engagement and Teamwork
Data Visualisation and Communication
Self-Awareness and Insight
Programming and Logical Thinking
Diversity and Inclusiveness
Strong self-organization and time management
Self-starter with the ability to manage deadlines, escalate blockers, and deliver high-impact work with minimal supervision
Comfortable working independently or collaboratively in a team
Effective collaboration across technical and non-technical teams
Analytical creativity and problem-solving mindset
Clear and concise communicator
* High attention to detail