Data Scientist I

Lexis Nexis - Risk Solutions; Dublin; On-site; EUR 45,000 - 70,000; Full time

Job summary

A leading company in risk solutions is seeking a Data Scientist to build predictive models for insurance pricing and fraud risk. The role involves complex statistical analysis, utilizing tools such as R and Python, and collaborating with various teams to enhance data-driven decision-making. This position offers a unique opportunity to advance your skills in a dynamic and supportive environment, contributing to cutting-edge solutions within the insurance sector.

Qualifications

• Experience in applied modelling and analytics in relevant industry.
• User experience of R, Python, SAS, SPSS or equivalent tools.
• Strong understanding of statistical methods.

Responsibilities

• Build and test statistical models for pricing and underwriting.
• Provide analytical results clearly to demonstrate product value.
• Research new technologies to enhance data science strategy.

Skills

Data mining

Statistical methods

Modelling techniques

Communication skills

Education

Degree in computer science, mathematics, statistics or quantitative methods

Master's Degree

Tools

R

Python

SAS

SPSS

Job description

About the Business: LexisNexis Risk Solutions is the essential partner for risk assessment. Within our Insurance business, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. Our solutions help drive better data-driven decisions across the insurance lifecycle, all while reducing risk and optimising processes. You can learn more about LexisNexis Risk at the link below.

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

Requirements:

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.

Learn more about the LexisNexis Risk team and how we work here

We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.

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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

At LexisNexis Risk Solutions, our businesses span multiple industries providing customers with innovative technologies, information-based analytics, decisioning tools and data management services that provide market-specific solutions. Approximately 11,100 employees in offices throughout the world support our brands by serving customers in more than 180 countries.

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LexisNexis Risk Solutions is part of RELX, a global provider of information and analytics for professional and business customers across industries. For more information, please visit www.risk.lexisnexis.com and www.relx.com .