Job Description

Introduction

Guardrisk is the undisputed market leader in cell captive insurance and risk solutions. We are renowned for our innovative approach to cell captive structures and other alternative risk transfer solutions for our clients. Guardrisk offers clients custom designed cover and is registered in South Africa as an insurer for all statutory classes of non-life and life insurance business.

Disclaimer

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

Role Purpose

The primary purpose of the Data Scientist is to derive business value from Data. The Data Scientist will be required to proactively fetch information from multiple data suppliers and then conduct sophisticated and systematic analysis of the data to extract actionable insights. The extracted data must be stored in an appropriate internal / external environment for which a database structure must be expanded as needed. There might also be an element of client engagement needed to communicate strategic results back to the client. The role requires the use of advanced analytics technologies and strong statistical methods, which potentially and over time could include the use of machine learning techniques and the use of predictive modelling. This is a data driven role and a solid understanding of statistics and data wrangling methods is required. There is a further requirement to use software skills. The ability to communicate findings as well as working methods across to both technical and business audiences is very important.

Requirements

Qualifications

Bachelor's Degree in sciences or engineering with a strong focus on computer science, statistics, mathematics and / or actuarial sciences



Fluency in Python, SQL and R



Beneficial if fluent in any of the following programming languages (C#.Net, C, C++, Visual Basic, SQL)

Experience

3-5 years of experience in a data warehousing, data sciences and/ or modelling environment



Good understanding of software languages and software infrastructure



Experience in working with and analyzing data



Insurance Industry Experience and Actuarial background

Duties & Responsibilities

Statistical and Mathematical Skills

Predictive modelling skills.



Knowledge of machine learning principles at a high level and ability to implement as and when needed.



Critical analytical thinking and attention to detail.

Programming and high-level understanding of cloud and web infrastructure

R, SQL, Python and JavaScript experience. High level of competency required in Python and SQL.



Beneficial to have experience deploying web applications to Azure.



Spark experience.



Version control principles.

Data modelling, analysis and loading data from any format and awareness of regulation surrounding personal data

This includes consuming data from either files/databases or online sources.



Validating data from multiple sources.



Data version control and data integrity for auditing.



Geo Spatial Analysis.



Using Business Intelligence tools like PowerBi to give insights into data findings.

Business Analysis

Analyze and document processes that translates into deriving value form data.



Understand the insurance operational environment.

Interpersonal Skills

Be able to self-organize.



Ability to self-motivate and work independently when needed.



Ability to work closely worth other stakeholders as successful output will depend on multiple technical areas.

Ability at a high level to understand insurance concepts both technical and non-technical

Break down insurance processes and document this as a set of business requirements for data presentation.



Interpret reinsurance treaties in the context of individual data sets.

Competencies

Data Wrangling

Understands that data can be messy and difficult to work with. Can unpack and treat imperfections in data (e.g., missing values, inconsistent string formatting) and enable data cleanliness.

Stakeholder engagement and Teamwork

Creates and maintains an open, positive working environment through collaborative engagement across the business. Understands how to interact with software developers, product managers and technical specialists and can obtain answers to deep questions during engagements.

Data Visualisation & Communication

The ability to communicate or describe findings and applied techniques to both technical and non-technical audiences.

Self-Awareness and Insight

Builds relationships with others effectively, deals with ambiguity, uncertainty, and pressure, and provides perspective in difficult situations.

Software infrastructure building

The ability to set up the team's data structures either internally or externally.

Diversity and Inclusiveness

Is sensitive to individual and cultural differences and demonstrates humility and an openness to engage people from diverse backgrounds and cultures to the mutual benefit of all parties concerned.

Data intuition

The ability to infer insights from large quantities of data. The ability to not just address business problems but to identify the right problems that have the most value to the organisation.

Independence

The ability to take ownership for own actions.