In order to be considered the following is required:

• Bachelor’s Diploma | Degree in one of the following fields: 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 as well as in data analysis and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn)
• Minimum of 4 years’ working experience in the following:

1. Power BI (essential)
2. Azure Data Factories (essential)
3. Azure Synapse Analytics (critical)
4. Python / R, C++, C#, Java (critical)
5. Microsoft SQL Server (critical)
6. T-SQL (critical)

• Effective communication skills, with the ability to collaborate with cross-functional teams and present complex ideas in a clear and concise manner
• Strong understanding of statistical concepts, data modelling techniques, and experimental design principles
• Must have prior experience developing business intelligence solutions in large or midsize companies
• Must be able to manage multiple tasks simultaneously and react to problems quickly
• Must have extensive experience with T-SQL
• Must be able to develop, maintain, review, and explain predictive models
• Understanding of the financial services industry desired, especially Insurance
• Experience using data visualization tools, e.g. Power BI
• 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)

Responsibilities:

• Experience with end-to-end data science use case implementation using Azure, Docker and FastAPI
• 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 including Ai and GenAi
• Build and operationalize predictive and propensity 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
• Automation of recurring processes and the monitoring thereof

Information displayed above not limited to advertisement.

Please consider your application as unsuccessful if you have not received a response within 14 days of submitting your application.