Data Scientist Data Scientist …

Macquarie Group
in Sydney, New South Wales, Australia
Permanent, Full time
Be the first to apply
Macquarie Group
in Sydney, New South Wales, Australia
Permanent, Full time
Be the first to apply
Macquarie Group
Data Scientist
An exciting opportunity for a Data Scientist to join our Risk Management Group's Data Analytics Team within our Risk Management Group. The Data Analytics team is responsible for leading, developing and deliver analytics assets and capabilities for Risk Management Group.

As a Data Scientist you will apply your broad skillset across data and analytics to understand business problems, create insights and envisage practical solutions within the Risk Management Group across several initiatives.

You'll work with the team to assist us in defining and delivering a roadmap of data analytics initiatives that identify efficiencies and unlock insights/opportunities for the group. You will have access to large data sets, giving you the ability to make a tangible impact with your analysis and will be responsible for the creation and implementation of enterprise wide machine learning models across the Risk Management Group.

The role will see you working with the team and other stakeholders to continuously monitor, manage and improve existing models to ensure their ongoing efficacy and identify opportunities for improvements through tuning or new methods/models.

Day to day your main tasks will be but not limited to:
  • Identifying relevant data sources, cleaning and preparing data.
  • Performing modelling and analysis using charting, descriptive statistics and machine learning including supervised and unsupervised methods.
  • Understanding the business's needs and required to create new models as well as work with the team to enhance and improve on existing models.
  • Communicating complex concepts simply and translate outputs into actionable insights for associated business stakeholders through both verbal and written communication (e.g. reporting etc).
  • Working closely with our Technology partners to implement best in class practices for Risk Management Group.
  • 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.

You will bring with you:
  • Prior experience in a hands-on data science role where you can demonstrate the ability to cleanse, combine and process data, as well as develop and implement supervised and unsupervised analytical models.
  • A curious and business outcome focused approach partnered with a problem-solving attitude.
  • Practical experience with machine learning and statistics, as well as prior expertise proficiency working with large data sets (Big Data) and appropriate software (Cloudera, Spark, Jupyter Notebooks etc.).
  • The ability to be a strong collaborator and be comfortable working with business stakeholders to identify and shape problems to be solved with data.
  • Proficient in using Python and/or R languages and in addition to this experience with NLP packages (Natural Language processing) would be a plus but not essential.

Additional Qualifications
  • A Graduate degree in a STEM discipline such as Data Science/Computer Science would be advantageous but not essential.

To express interest, please apply online today.

The Risk Management Group is an independent, centralised unit responsible for assessing and monitoring risks across Macquarie. This includes market and liquidity risk, credit risk, compliance risk and operational risk. Risk Management Group personnel liaise closely with all operating areas to ensure risks are understood and properly managed.

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Macquarie understands the importance of diversity and inclusion - our long history of success has come from being different. At Macquarie we value the innovation and creativity that diversity of thought brings. The one thing we all have in common is our focus on high performance. If you're capable, motivated and can deliver, we want you on our team.

Advertised: 16 Oct 2019 AUS Eastern Daylight Time
Applications close:

Company Overview

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