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RGI is an Independent Software Vendor, a European leader in the digital transformation of Insurer.
It has been active for 30 years as a solid point of reference for the development and implementation of systems for insurers, Bancassurance, agents, brokers, financial consultants and so on.
With a team of 800 professionals specialised in IT and the insurance business in 12 offices in Italy, Ireland, France, Germany, Tunisia and Luxembourg, RGI has digitised the business of 103 insurance companies and 300 brokers across the EMEA region.
RGI has always paid special attention to technological development and the quality of the tools it offers, in order to ensure not only high performance, but also speed of implementation, short release times and rapid and effective support services.
We want to be a reliable partner and one of the most innovative and influential companies in the insurance industry, able to support our customers at all stages of organisational technological innovation and in the constant changes imposed by the market today.
RGI has an exclusive vertical focus on the insurance industry and specialises in the development and implementation of modular Policy Administration System insurance solutions for all distribution channels and all business lines.
Its strong orientation towards technological innovation and its exclusive focus on the insurance industry are the foundations that have enabled RGI to develop and diversify its products, achieving excellent levels of quality in the solutions and high value-added services it provides.
The selected candidate will work in the R&D Innovation Department, as part of the Data Analyst team with other experts in the field and will report to the Data Analyst Lead.
The main activities required to the selected candidate aims at consolidating and widening the general knowledge and technological knowhow of RGI in the field of the Business Intelligence and Predictive Analytics.
Excellent experience in academic research, with a deep understanding of statistical and predictive analytics concepts.
The candidate will have a Master’s Degree in Computer Engineering, Applied Statistics, Math, Physics or a related quantitative discipline (a Ph.D. is recommended)
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