Data Scientist/ Modelling Analyst

  • Location


  • Discipline:

    Credit Risk & Analytics

  • Job type:


  • Salary:

    £45,000 - £55,000

  • Consultant:


  • Email:


  • Job ref:


  • Published:

    over 2 years ago

Job Description- To support the Decision Science-Strategy team in the identification, development and testing of innovative, alternative collections strategies and processes to continuously improve performance of purchase or contingent portfolios in the UK Group

This Client does not provide sponsorship.

Key Responsibilities of the Data Scientist/ Modelling Analyst-

  • Development of the Modelling infrastructure; which includes modelling datasets, model scoring and model monitoring
  • Development of statistical models, (predictive and descriptive) using internal and external data to support customer contact activity.
  • Analyse data to  produce, evaluate, interpret and analyse a range of statistical and written information in order support recommendations that will have a positive impact on policy and strategy
  • Support the identification of value adding opportunities, through proactive analytics into any variances in performance and identify underlying causes.
  • Contribute towards regular updates of any business improvement solutions.

Ideal knowledge and experience of the Data Scientist/ Modelling Analyst-

  • Experienced in developing models (predictive & descriptive) using techniques such as Logistic Regression, Linear Regression, CHAID, Random Forests, Cluster Analysis, Discriminant Analysis
  • Experience of working in a heavily regulated environment.
  • Experience in using internal and external data and insight to support recommendations that shape business strategy and improve performance
  • Ability to work as part of a team, pro-actively, multi-task and deliver
  • Competent communication, interpersonal and listening skills – ability to communicate at all levels
  • Ability to present complex and detailed data in a format that aids debate and discussion across the business
  • Experience in the use of Business Intelligence, Analytical and Statistical packages (e.g.  SQL, SAS, SAP Business Objects, Cognos, Tableau, R)
  • Fully proficient with advanced levels of MS Excel and PowerPoint
  • High attention to detail