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https://risk.lexisnexis.com/insurance
About our Team: You will part of a small team assisting the business with statistical analysis and building predictive models for insurance pricing, underwriting and fraud risk.
About the Role: We are looking for a Data Scientist to conduct statistical analysis and build predictive models for insurance pricing, underwriting and fraud risk. The ideal candidate will have experience in data mining, statistical methods, and modelling / scoring techniques. They will balance day-to-day analytics assignments, research experiments and will contribute to the advancement of the global data science group.
Responsibilities
- Building and testing insurance pricing, underwriting and fraud risk statistical models, consulting in support of existing and new customer sales
- Providing complex analytical results in clear, simple messaging to evidence the value provided by our products
- Following modelling best practices and provide feedback on ways to enhance current processes
- Providing technical support and be a resource to internal partners in Product, Sales and Technology teams
- Researching new technologies and bring forward new ideas to the group
- Supporting and help to shape our data science strategy
- Have degree in computer science, mathematics, statistics or quantitative methods (or equivalent experience). Master's Degree
- Be able to demonstrable experience or knowledge of applied modelling and analytics experience in applicable industry
- Have good understanding of statistical methods applied to data analysis
- Have user experience of R, Python, SAS, SPSS or equivalent analytic software.
- Have understanding of various statistical methodologies including linear regression, logistic regression, and other advanced analytic techniques
- Have good written communication skills, including the ability to describe statistical results to non-statistical audiences.
- Experience processing large data sets and matching/merging multiple data sets.
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