Junior Data Scientist

Description:

• Develop and maintain an understanding and a sound base knowledge of life & health insurance and reinsurance and the technical requirements for appropriate data management.
• Automation of data extraction, developing data pipelines and data warehouse designs
• Understanding advanced analytics and identifying potential business cases for its applications
• Application of statistical and machine learning (supervised and unsupervised) methods
• Interpretation of model outcomes in a business context and advanced data visualizations
• Work with structured databases containing data from multiple sources, at various granular levels, to deliver good-quality analytics and visualization projects
• Validate data to ensure confidence in data quality.
• Assist team members in data extractions for ad-hoc projects to support proper risk management
• Provide underlying technical support to the actuarial team in monthly reserving data preparation, and consolidations.
• Create new or modify existing reports to address evolving needs.
• Add more flexibility to the existing monitoring tools where required.
• Analyze the root cause of performance movement through drill-down exercises.
• Highlight data discrepancies and independently escalate with internal and external stakeholders describing underlying risks and reaching a successful and workable solution.
• Drive automation of existing data processes to improve underwriting efficiency
  
   

Your Profile
 

• 1-2 years of experience as a working student or a data analyst preferably within the insurance/reinsurance/actuarial field.
• Bachelor’s degree in Computer Science, Mathematics, Statistics, Actuarial Science, and/ or a comparable degree with a sound IT and mathematical background
• A master’s degree in one of the mentioned subjects would be an advantage
• Good knowledge of R, SAS, Power BI, Tableau, or Online insurance data platforms will be a strong advantage.
• Experience in data warehouse architectures and ETL & CDC tools, such as Informatica, Azure Data Factory, or similar
• Data modelling (understands transactional vs. analytical models, graphs structures, and document stores)