2025 Risk Data Scientist Intern

Details of the offer

POSITION OVERVIEW The Risk Data Analytics group reports through the Chief Risk Officer and uses machine learning techniques to develop predictive models for policy-level transactions and human behaviors.
The models are used to develop and price retail products and institutional reinsurance deals, monitor related risk, and to assist in forecasting and financial reporting.
The group has a unique vantage point into nearly all aspects of the enterprise and is actively enhancing its capacity, continuing to grow with the whole company.
The successful candidate will have an opportunity to work on a variety of projects depending on skill set, interest, and personal goals, and to collaborate with other teams with functions mentioned above.
RESPONSIBILITIES Implementing machine learning and optimization toolsDeveloping supervised and unsupervised machine learning modelsAssisting with ad hoc data analytics projectsAssisting the team on developing automated data pipelineQUALIFICATIONS Strong academic record in pursuit of a Bachelor or Master's degree in top universities with concentrations and/or interests in Computer Science, Engineering, Mathematics, Economics, Finance, or other quantitative field (minimum 3.5 GPA)Graduating in December of 2025 or May of 2026Background in a technical or scientific field and at least two year/four semesters of programming experienceKnowledge of Python, data structure, statistics, regression, machine learning are requiredKnowledge of high-performance computing, such as PySpark, are preferred but not requiredKnowledge of Generative AI and relevant tools, such as AWS SageMaker, and Langchain, are preferred but not requiredStrong analytical, organizational, and communication (written and verbal) skillsPro-active, detail oriented, and deadline driven; possess excellent documentation and analysis skillsExtraordinarily strong Excel skills are highly valued but not requiredThis position is not eligible for visa candidates now or in the future.

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Nominal Salary: To be agreed

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