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Decision Science Analyst

Job LocationLondon
EducationNot Mentioned
Salary£40,000 - £55,000 per annum
IndustryNot Mentioned
Functional AreaNot Mentioned
Job TypePermanent, full-time

Job Description

Decision Science AnalystUp to £55,000LondonIm currently seeking a Senior Analyst for a Predictive Modelling and Advanced Analytics role at an exciting financial services brand. If you are a bright Analyst with strong academics and an excellent record of problem solving through data within a Financial Services environment then this could be the challenge youve been looking for.Use data and apply advanced analytics to accurately predict asset valuations in a Credit Risk environment. With end to end ownership, youll present your own recommendations to investment committees and stakeholders. This is the perfect role for someone looking for an opportunity to learn and grow, with increased responsibility and accountability on offer!THE ROLE

  • Use machine learning and advanced analytical techniques (KNN, Random Forests, XGBoost, etc.) to accurately predict and value Credit Risk and increase profits
  • Develop predictive models, e.g. Scorecards, using statistical tools and techniques to increase efficiency and profitability across international markets
  • Present your analysis, valuations and predictions to the Decision Committee and Stakeholders
  • Dig into data and raw information through statistical analysis to discover trends and patterns that can be used to extract valuable business insights.
  • Actively push the boundaries in modelling, predictive analytics and business insights to ensure the latest developments in data science and analytics are leveraged
  • YOUR SKILLS AND EXPERIENCEThe successful candidate will likely have the following skills and experience:
  • Master degree (preferred) in a STEM or similar discipline
  • Previous experience developing predictive models or applying machine learning algorithms
  • Proven stakeholder management experience
  • Experience managing databases with SQL
  • Experience in using statistical computing languages R, Python or SAS to manipulate data and draw insights from those data sets
  • Experience working in a data-driven or quantitative role within financial services, ideally within Credit Risk
  • Strong communicator with fluency in English (European languages an advantage)
  • HOW TO APPLYEmail your CV or use the apply feature on this pageKEYWORDSCredit Risk Analytics, Credit Risk Models, Basel, AIRB, Scorecards, Decision Science, Machine Learning, Data ScienceSAS, SQL, PD, LGD, EAD, IFRS9, Logistic Regression, Decision Tree, Probability of Default, Exposure of Default, Loss Given Default

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