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Senior Data Scientist - Tier 1 Banking - London

Job Title: Senior Data Scientist - Tier 1 Banking - London
Contract Type: Permanent
Location: London
Industry:
Salary: £85000 - £95000 per annum + Benefits & Bonus
Reference: BBBH13979_1488558349
Contact Name: Sarah Spooner
Contact Email: sarah.spooner@twentyrecruitment.com
Job Published: March 03, 2017 16:25

Job Description

Data Scientist required for Tier 1 Bank to work on greenfield innovation projects within their London HQ. This is a hugely exciting time for the Data Scientist to join a rapidly growing department as an SME within the field. The Data Scientist will have expertise in data science tools such as R, SQL, Python, Spark and other Big Data technologies. These roles are far from "business as normal"- they are heavily focused on research and development, allowing you the artistic freedom to apply the best technologies and techniques to your work as well as gaining exposure to all areas of the organisation. This includes Investment, Group and Retail. The Company has truly bought into Data Science, backing this department to grow.

Some of the key aspects of the role include:

  • Mentoring team members in the use of data science tools such as R, SQL, Python, Spark and other Big Data technologies.
  • Testing and designing algorithms allowing for the automation of insight; both business and customer.
  • Defining data needs for teams across the business and acting as both an ambassador and SME.
  • Guiding stakeholders to implement new algorithms and methods based on your work.
  • Creating and validating models both statistical and machine learning - including predictive analytics, segmentation modelling, recommendation algorithms.

Technical Skills: R, Python, Scala, Spark, SAS, SQL

The successful Data Scientist will be "seasoned" in their craft, having clear examples of extracting, transforming and working with complex data sets and the application of advanced analytical techniques. The Data Scientist will ideally have an emphasis on Python and R and the use of predictive models and machine learning.