Data Scientist

About the Business: LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below, risk.lexisnexis.com

  About our Team: You will part of a small team assisting the business with statistical analysis and building predictive models for credit, fraud, and risk.

  About the Role: We are looking for a Data Scientist to conduct statistical analysis and build predictive models for credit, fraud, and 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 credit 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

At LexisNexis Risk Solutions, having diverse employees with different perspectives is key to creating innovative new products for our global customers. We have 30 diversity employee networks globally and prioritize inclusive leadership and equitable processes as part of our culture. Our aim is for every employee to be the best version of themselves. We would actively welcome applications from candidates of diverse backgrounds and underrepresented groups.

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: .

At LexisNexis Risk Solutions, our seven brands span multiple industries providing customers with innovative technologies, information-based analytics, decisioning tools and data management services that provide market-specific solutions. Approximately 10,000 employees in offices throughout the world support our brands by serving customers in more than 190 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 and .

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