Quantitative Analyst: Credit Risk Data Science
The major focus of this exciting opportunity is the research and development of cutting edge behavioural/machine learning models for Risk Decisioning
Summary about this job
Compliance & Risk
Company: Mars Recruitment
Location: Sydney
Work type: Full Time
Salary: n\a
Phone: +61-7-2201-7480
Fax: +61-8-2192-7536
E-mail: n\a
Site: n\a
Detail information about job Quantitative Analyst: Credit Risk Data Science. Terms and conditions vacancy
- Great move from Credit Risk into Data Science
- 60% R&D / 40% Operationalising / 0% running reports
- Collaborative team that enjoy being creative
The major focus of this exciting opportunity is the research and development of cutting edge behavioural/machine learning models to find previously unidentified patterns of behaviour and risk vector correlations to enhance the bank’s risk decision making.
As a key member of the Team, you will have the opportunity to help drive strategic changes in Risk quantification and decisioning on the various financial risks the bank faces through the design and build (in conjunction with Quant Dev.) of various novel behavioural modelling, implementation of Neural Networks and various deep learning methodologies.
You will be responsible for:
- Performing empirically derived analysis to understand business performance, identify improvement opportunities, and develop strategies and recommendations
- R&D and implementation of risk models and scorecards utilising a range of statistical & machine learning techniques
- The accurate construction and evaluation of data sets, graphs, and reports and be able to communicate the same to your team and your stakeholders
- Be required to document all your processes and analysis for independent validation
- Contribute to the development of the analytics team and expanding their data analytics capabilities
You will need the following experience and skills to be successful:
- Understanding of credit risk
- Experience in statistical or machine learning approaches to data analysis and data mining
- Experience using the following: R, SQL, SAS, Python (Essential)
- A tertiary degree in finance, actuarial or related discipline
- Exposure to machine learning techniques
- Exceptional organisational and time management skills
- Strong written and verbal communication skills
- Ability to work both autonomously and as an active team member
- Proven ability to translate technical detail into terminology that non-technical teams can understand and use