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Data Scientist - Pricing Modelling

Job Reference: asc - 2 - 13.02.18

Employer/Agency Name: Aspire Data Recruitment

Location: Durham

Job Sector: Accountancy, Banking, Finance

Salary/Package: £30k-£40k

Duration: n/a

Date Posted: 13/02/2018

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Job Title:                           Data Scientist - Pricing Modelling
Location:                          Durham
Salary:                               to £40,000 + bonus & benefits

We have a fantastic opportunity for a Data Scientist to join our client, a start-up digital bank, and help it to drive forward its analytics capability.

In this newly created role the Data Scientist will: 

- Develop and implement various types of predictive models, segmentation strategies, optimisation algorithms and data mining analysis - including predictive models, regulatory models, scorecards and simulation models.  Delivering predictive models that generate significant uplift in business performance and/or provide an enhanced customer experience.
- Delivering end-user solutions to enable customers to utilise predictive models to perform what-if analyses. 
- Monitoring and maintaining models to ensure that they remain fit for purpose
- Providing peer review and challenge to analysis and models developed by other members of the team.
- Delivering ad hoc analysis to provide key insight into business performance

This role will give the Data Scientist a rare opportunity to work with all functions within the bank, giving insight to a wide range of activities, working with external data and analytics suppliers where required. Furthermore, as the business grows, the requirements for analytics will expand significantly, providing opportunities to expand your own capabilities.   

What do you need to apply?

- Degree in a numerate discipline (e.g. Maths/Statistics/Economics or similar) with a high degree of statistics. 
- Sound understanding of one or more of the following modelling techniques - collaborative filtering, support vector machines, neural networks, linear and logistic regression, decision trees, random forests
- Experience of data analysis tools, such as SQL, R, Python,  SAS or similar
- Good working knowledge of MS Excel
- Good communication skills - able to present analysis at all levels of the business and to non-specialists
- A self-starter with excellence time management skills

In addition, skills in the following areas would be beneficial...

- Data visualisation with tools such as Tableau, Shiny or knowledge of Scala programming language.
- Experience of delivering predictive models to support application or behavioural credit risk scoring, IRB, IFRS9, scorecards, pricing and price elasticity, or product propensity models. .
- Delivering analysis and/or reporting in a Financial services environment, 
- Experience in dealing with large data sets

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