Data Scientist - Finance - Fraud & Lending

Recruiter
Harnham
Location
Farringdon
Posted
14 Apr 2018
Closes
17 May 2018
Sector
Accountancy
Contract Type
Permanent
Hours
Full Time

Data Scientist - Fraud & Lending

London

£70,000 + 10% Bonus

THE COMPANY

My client is looking for a commercially experienced Data Scientist, who is looking to work on the latest fraud detection problems within the lending space. This traditionally risk-averse lender, is looking for someone experienced in ML to be able to automate complex processes that historically took a huge amount of time and manual effort!

Currently, this company has proven gone from strength to strength and the Head of Analytics plans to continue growing the team, as it continues to prove its commercial success. This role really requires somebody who can think big, and generate revolutionary ideas.

THE ROLE:

  • Work alongside the experienced Analysts and Scientists to create ML solutions
  • Provide actionable insight from complex, constantly evolving data-sets
  • Build models based upon comprehensive data sets
  • Help develop and mentor Junior Data Scientists and Analysts
  • Manage Data Science projects from start to finish
  • Work with non-technical stakeholders to help develop policy

YOUR SKILLS AND EXPERIENCE:

The essential requirements of a Data Scientist in this role are:

  • Commercial Experience deploying ML algorithms
  • Willingness to work entirely hands-on using ML techniques
  • Academic background in a scientific/quantitative/economic disciplines
  • Multiple years of coding experience in Python and use of ML toolkits
  • Ability to work autonomously
  • Strong communicator
  • Applied Mathematical Background

THE BENEFITS:

  • Flexible working
  • Flexible holiday package
  • Strong pension package
  • Latest equipment
  • Competitive salary and bonus package

KEYWORDS

Python, SQL, e-commerce, economics, data science, data engineer, development, management, research, implementation, programming, visualisation, technology, problem-solving, R&D, deep learning, deep-learning, recommendation, experience, customer, tailored, startup, start-up, start up

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