Data Scientist - Risk Analytics - Banking

Competitive
Permanent
Sydney CBD
03 Dec 2019
BBBH746678

Apply now!

This role will require you to have solid experience with risk analytics across the areas of scorecards, credit risk models. and validation But unlike many other roles this will be done in a cutting edge big data environment with a team of high performing data experts consisting of data scientists, big data engineers and data visualisation specialists.

The ideal candidate will have:

  • Strong experience developing retail credit risk modelling
  • Must have model validation expereince (essential)
  • Programming skills with open source tech such as r, or python
  • Application scorecard development experience would be adavantagous
  • Exceptional commercial acumen with the ability to see the bigger picture
  • Strong communication skills
  • Experience with statistical techniques for analyzing financial data, including: sampling, optimisation, logistic regression, linear regression, decision tree analysis, etc
  • Practical experience or at least interest in machine learning, cloud tech would be highly advantageous
  • Relevant industry experience

In exchange you will be part of industry thought leaders in who are known as the leaders in this space. They have a real family atmosphere and a strong desire to shake up the industry and push the boundaries as to what can be done in data science.

For more information about the data space or contact Leon via email to lyoung@morganmckinley.com.au

Leon Young's picture
Senior Consultant | Analytics
Sydney +61 (0)2 8986 3147 | lyoung@morganmckinley.com.au