Data Scientist (Business Intelligence) Mmh240627-1

Guardrisk Group; Gauteng; On-site; ZAR 600 000 - 800 000; Full time

Job summary

A leading insurance firm in Gauteng is seeking a Data Scientist (Business Intelligence) to leverage data for insightful decision-making in their operations. The ideal candidate will have strong programming skills in Python and R, and a deep understanding of data visualization and machine learning. Key responsibilities include analyzing complex datasets, developing predictive models, and collaborating with cross-functional teams to enhance BI solutions.

Qualifications

• Proven experience working as a data scientist or in a similar role, preferably in insurance.
• At least 4 years working experience in Power BI, Azure Data Factories, and Azure Synapse Analytics.
• Strong understanding of statistical concepts and data modeling techniques.

Responsibilities

• Participate in the analysis, design, and development of reporting and analytics platforms.
• Analyze datasets to identify trends, patterns, and correlations.
• Develop, implement, and validate machine learning algorithms.

Skills

Python

R

Java

Power BI

T-SQL

Data visualization

Machine learning

Statistical analysis

Education

Bachelors degree or diploma in Informatics, Computer Science, Statistics, Mathematics or Information Technology

Tools

Azure Data Factories

Azure Synapse Analytics

Microsoft SQL Server

TensorFlow

PyTorch

Hadoop

Spark

Google Cloud Platform

Job description

Join to apply for the Data Scientist (Business Intelligence) MMH -1 role at Guardrisk.

Role Purpose

As a data scientist, you will play a key role in leveraging data to drive insights, inform decision-making, and enhance our life and non-life insurance operations. You will work closely with cross-functional teams to develop innovative data-driven solutions that address business challenges and improve overall performance.

Qualifications

• Bachelors degree / diploma in Informatics, Computer Science, Statistics, Mathematics or Information Technology.
• Proven experience working as a data scientist or in a similar role, preferably in the life and non-life insurance industry.
• Proficiency in programming languages such as Python, R, or Java, and in data analysis and machine learning libraries (TensorFlow, PyTorch, scikit-learn).
• At least 4 years working experience in the following: Power BI (essential), Azure Data Factories (essential), Azure Synapse Analytics (essential), Python / R, C++, C#, Java (critical), Microsoft SQL Server (critical), T‑SQL (critical).
• Effective communication skills, ability to collaborate with cross-functional teams and present complex ideas clearly.
• Strong understanding of statistical concepts, data modeling techniques, and experimental design principles.

Duties and Responsibilities

• Participate in the analysis, design, development, troubleshooting and support of the reporting and analytics platform.
• Analyze complex datasets to identify trends, patterns, and correlations.
• Generate and test working hypotheses, and interpret results to provide actionable insights.
• Develop, implement and validate machine learning algorithms and statistical models.
• Build and operationalize predictive models to unearth hidden insights.
• Collaborate with actuaries, underwriters, and other stakeholders to integrate data science solutions into existing workflows and processes.
• Develop BI solutions using SQL, ETL scripting, business intelligence tools, database programming and reporting tools on the Microsoft BI Stack.
• Build scalable data pipelines and infrastructure for collecting, processing, and analyzing large volumes of structured and unstructured data.
• Automate recurring processes and the monitoring thereof.
• Have prior experience developing business intelligence solutions in large or midsize companies.
• Manage multiple tasks simultaneously and react to problems quickly.
• Have extensive experience with T‑SQL.
• Be able to develop, maintain, review, and explain predictive models.
• Understand the financial services industry, especially insurance.
• Use data visualization tools, e.g., Power BI.
• Have excellent problem‑solving skills and the ability to translate business requirements into actionable insights.
• Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud platforms (e.g., AWS, Azure, Google Cloud Platform).