As a Data Scientist in the Model Validation and Tuning function, you will apply your broad skillset across data and analytics to understand business problems, create insights and envisage practical solutions within the Risk Surveillance across several initiatives. You’ll be responsible for the development, testing, implementation and tuning of detection capabilities and solutions within Risk Surveillance. The role is focused on using both established and emerging analytical capabilities to improve the efficiency and effectiveness of the Risk Surveillance detection solutions.
You will have access to numerous data sources, giving you the ability to make a tangible impact with your analysis and you will be responsible for the creation and implementation of machine learning models. You will also deliver data-driven insights by preparing, analysing and interpreting results and data from the risk surveillance models while working collaboratively with a range of stakeholders across all regions to understands their business and regulatory requirements to tune the risk surveillance detection models.
You’ll also identify relevant data sources, clean and prepare data as well as perform modelling and analysis using charting, descriptive statistics and machine learning including supervised and unsupervised methods. You’ll work collaboratively with a range of stakeholders to design, develop and implement new and improved models across all regions and partner closely with our technology partners to implement best in class practices for Risk Surveillance. You’ll also provide thought leadership on key developments in the data science industry and help to evangelise the capabilities in this area through regular stakeholder engagement and training.
We are looking for someone with prior experience in a hands-on data science role who can demonstrate the ability to cleanse, combine and process data, as well as develop and implement supervised and unsupervised analytical models. Experience with Project management, handling multi-initiatives with limited resource and the ability to showcase strong stakeholder management skill is also preferred
To be successful in this role you should have 5 to 6yrs of practical experience with machine learning and statistics, as well as proficiency working with big data and appropriate software (Cloudera, Spark, Jupyter Notebooks and similar). You will be proficient in using Python and/or R languages. Experience with NLP packages (Natural Language processing) and proficiency in using Alteryx / SQL and Power BI would be a plus but not essential. A Graduate degree in a STEM discipline such as Data Science/Computer Science would also be advantageous but not essential.
If this sounds like the right opportunity for you to further your career, we’d love to hear from you and encourage you to apply via the link provided.
About the Risk Management Group
The Risk Management Group (RMG) is an independent, centralised unit responsible for ensuring all risk across Macquarie are appropriately assessed and managed. Its divisions include Behavioural Risk, Compliance, Credit, Financial Crime Risk, Internal Audit, Market Risk, Operational Risk, Regulatory Affairs and Aggregate Risk, and RMG Enterprise Support.
Our commitment to Diversity and Inclusion
The diversity of our people is one of our greatest strengths, and in combination with our inclusive environment, it enables us to deliver innovative and sustainable outcomes for our people, clients, shareholders and communities. From day one, you'll be encouraged to be yourself and supported to perform at your best. If our purpose of ‘empowering people to innovate and invest for a better future’ is as inspiring to you as it is to us, please apply. With the right technology, support and resources, our people can work in a range of flexible ways.
We are committed to providing a working environment that embraces and values diversity and inclusion. We encourage candidates to speak with a member of our recruitment team if you require adjustments to our recruitment process to support you, and the type of working arrangements that would help you thrive.