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Intern data scientist (80-100%)

Zürich
Praktikum
Swiss Reinsurance Company Ltd
Data Scientist
Inserat online seit: 10 Juni
Beschreibung

Ph3About the role /h3 pAre you passionate about technology and would love to join our highly skilled global team? With this 4–6-months internship, you will have the possibility to integrate into a team of Data Scientists and to contribute to developing analytics services and solutions in tight collaboration with internal business experts and external clients. The internship is expected to start in Spring 2024. /p h3Responsibilities Key Tasks /h3 ul liSupport in developing impactful data science products by contributing to the end-to-end delivery, including data engineering visualisation, machine learning modelling and model interpretation/monitoring /li liDevelop toolboxes and solutions that can be re-used across projects /li liContribute actively to the team by joining and doing knowledge sharing session, joining the team events, support team efforts, hackathons etc. /li /ul h3About the team /h3 pThe Advanced Analytics Centre of Expertise (AA CoE) is part of the Group Data Analytics Services. The AA CoE implements Swiss Re`s Technology Strategy and supports its business functions in generating insights and creating data driven products solutions, be it with our internal business partners or directly with our external insurance and corporate clients. /p h3About you /h3 ul liBachelor or freshly graduated from a Master’s degree in a relevant technical discipline: e.g. mathematics, statistics, computer science, engineering, physics /li liStrong knowledge in statistical modelling and/or machine learning /li liOpen and curious, eager to learn about new technologies and Machine Learning /li liEager to collaborate in a team setting /li liGood communication skills in English, ability to present ideas and explain a model in non-technical terms /li /ul h3Nice to have: /h3 ul liHands‑on experience with Python and/or R, SQL /li liKnowledge in software/data engineering (e.g. code versioning, distributed computing…) /li liKnowledge on large language models /li /ul /p #J-18808-Ljbffr

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