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Data scientist - credit risk & fraud

Slough
Square One Resources
Data scientist
Posted: 12 June
Offer description

Job Title: Data Scientist - Credit & Fraud Risk

Location: Cardiff/Remote

Salary/Rate: £500 - 560 per day inside IR35

Start Date: June

Job Type: Initial 12-month contract



Company Introductio

nWe have an exciting opportunity now available with one of our sector-leading data analytics clients! They are currently looking for a skilled Data Scientist to conduct statistical analysis to support product strategy decisions


.
Job Responsibilities/Objectiv

esThis role is focused on supporting day-to-day analytical activities across customer portfolios, including credit application assessments, standard financial and risk analysis, and product-related analysis. The individual will also contribute to research and development initiatives, monitor and evaluate model performance, and support the migration of existing analytical processes to cloud-based platforms. Overall, the role requires a strong blend of analytical capability, technical understanding, and adaptability to evolving tools and environment

s.The ideal candidate will have experience in data mining, statistical methods, and modelling / scoring technique


s.
Required Skills/Experie

nceThe ideal candidate will have the followi

ng:Have experience of independently running analysis of large datasets, producing results and presenting these to business partners with support of data science pee


* rs.
Credit and fraud modelling experi
* enceHave degree in computer science, mathematics, statistics or quantitative methods (or equivalent experien
* ce).Have good understanding of statistical methods applied to data analy
* sis.Have user experience of Cloud capabilities, preferred Databri
* cks.Have user experience of coding languages for data science and machine learning (e.g. Python,
* R).Have good written communication skills, including the ability to describe statistical results to non-statistical audien
* ces.Experience processing large data sets and matching/merging multiple data s


ets.

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