Data Scientist - London

This vacancy is now closed
£80000 - £100000 - Information Technology
Ref: 121 Date Posted: Sunday 15 Apr 2018
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Lead the development of a data science team to support and drive enhanced pricing capabilities and asset management strategies across all European credit investments consisting of unsecured and secured consumer, SME and mortgage debt.

 

Responsible for building an expanded data warehouse and applying advanced data mining and analytics to optimise investment returns whilst maintaining the highest standards of reporting, performance monitoring and on-going analysis / review.

 

Key Responsibilities and Accountabilities:

 

  • Leading/managing a team of data scientists including developing and coaching junior team members in UK and India
  • Creating, maintaining and owning a variety of predictive models for unsecured SME and consumer loan portfolios to support pricing and asset management
  • Collaboration with Developers and Business Analysts to deploy models and scorecards across the organisation
  • Creating, maintaining and owning reporting tools, working in close collaboration with the Asset Management team, to closely monitor portfolio performance against underwritten assumptions and allow servicing strategies to be more dynamically adjusted  
  • Understanding and improving the organisational data infrastructure
  • Designing, evaluating and developing new datasets for the business including incorporating external data sources from credit bureaus and other providers
  • Integrating existing disparate datasets into the data infrastructure
  • Performing data mining using cutting edge techniques whilst maintaining best practice to increase pricing competitiveness for new deals and identify value enhancing servicing strategies for existing portfolios
  • Ensuring all outputs/management information communicated in a business-related manner, ensuring a constant link between how data inputs and outputs affect business strategy and outcomes

 

 

Qualifications and Experience:

 

  • Graduate or Post-Graduate (BSc/Msc/Phd) in a quantitative field
  • 4+ years technical experience within a commercial environment, ideally financial services-based
  • Strong mathematical and statistical background (including classical statistical methods – regression, clustering, decision trees etc.)
  • Excellent understanding of data mining and machine learning techniques
  • Hands on experience with data manipulation/statistical tools such as R, Python (Anaconda), SAS, Spark, Hadoop
  • Experience with SQL and NoSQL databases is desirable
  • Knowledge of data visualisation tools (Qlik, Tableau, PowerBI)