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Royal London GroupSenior Data & Modelling Analyst - EdinburghSalary c. £35,500 - £53,300 + Excellent BenefitsBenefits - Bonus, 28 days holiday + stats, contributory pension Royal London is the largest mutual life, pensions and investment company in the UK, with Group funds under management of £100 billion. Group businesses provide around 9.1 million policies and employ 3,253 people. (Figures quoted are as at 31 December 2016).Founded as a Friendly Society in a London coffee shop in 1861, Royal London started out with the aim to help people avoid the stigma of a pauper's grave. Since then we have been helping people help themselves and are committed to delivering the best value for customers and putting members first.We have an exciting opportunity for a Senior Data & Modelling Analyst to join the Analytics team within Protection Proposition in Edinburgh.The main purpose of this role is to lead and deliver analytics projects within the Protection business in order to improve the way we do business. We are currently pursuing a number of innovative applications of predictive analytics and machine learning in the Life Insurance market and this role will be at the centre of these developments.This technical role will be working in an Agile environment and offer the successful candidate the ability to take ownership and responsibility for managing their own modelling remit/projects; delivering detailed schedule of works from initial briefs.Key Accountabilities:Lead the delivery of analytics projects in Underwriting, Fraud Detection, Market and Distribution Analysis, and Commercial and Risk ManagementApplying cutting edge statistical and machine learning techniques to support critical decision making in the businessDeveloping analytical and automated approaches to gathering and analysing competitor and market insight, eg web crawling, text analytics, socio-demographic analysisOwn the curation of the team's code libraryKeep abreast of new developments in Analytics, Predictive Modelling and Machine LearningBe responsible for carrying out Continuous Improvement in our approachSupport the wider team and Business Unit with requests for ad hoc AnalysisDevelop self-service reporting, dashboarding and analytics to allow customers to meet these needs themselvesAct as the go-to person in the business unit and wider division on questions relating to Analytics, Predictive Modelling and Machine LearningBe an advocate of these techniques and the potential for their application in our Business Unit and DivisionKey Skills & experience:The successful candidate will have a proven record delivering analytics projects within financial services (insurance preferable) and possess a broad understanding of BI and analytics tools, including Tableau, SQL and R - including Microsoft R Server.Undergraduate degree/MSc/PhD in mathematics, statistics, economics, engineering, physics or other subject area with significant mathematical contentExperience of leading analytics projects to a successful conclusionAbility to collate, analyse and distil data into insight in order to solve business problemsExperience of manipulating and analysing large data setsExperienced in the use of predictive modelling, machine learning and data miningExposure to parallel computingAbility to communicate result using data visualisation tools such as TableauExperience working in an agile environment, eg Scrum, Kanban etc.Foundational understanding of the UK Life and Pensions marketMethodical and inquisitive approach to workOpenness to new ways of thinking and acquiring new skills - eagerness to learn new tools and techniquesThoughtful process of analysing data and problem solving to reach a well-reasoned and actionable resultsWillingness and ability to mentor junior team membersAbility to communicate and present results to both technical and non-technical audiencesSolid business and organisational skills, and demonstrate leadership in the use of data and analyticsAbility to liaise with and manage internal customers and senior managersTo apply, please use the 'Apply Online' link below.For any further queries regarding the role, please contact (see below)