VIC, Melbourne, AU
6d ago

As Analyst you will develop deep technical and broad commercial skills by being exposed to, and working on a wide variety of internal projects.

Working as part of a large, sophisticated analytics team, you will be will be required to :

  • Manipulate and analyse data for the development and validation of predictive models in the areas of credit risk, demographics, marketing, fraud and ratings, in distributed computing environment
  • Monitor Equifax's cutting edge scorecards and risk tools
  • Create business case and analytic insight materials that show the value of predictive modelling and visualise the insights
  • Conduct ad hoc queries such as bureau insights, testing solutions
  • Quality check own and others' outputs
  • Maintain documentation that supports Analytics platform of databases, data products and analytical solutions.
  • What are we looking for?

  • Demonstrate technical competence and demonstrates business focus
  • Strong numeracy skills
  • Strong statistics or analysis skills
  • Experience in SAS, Python, SQL, R, Python or related statistical computing language
  • Proficient in most Microsoft Office suite
  • Nice- to Haves

  • Experience in a data analysis / risk environment
  • Database management and manipulation skills
  • Experience in statistics / mathematical modelling or operations research
  • Experience in SAS, Python, SQL or R computing languages
  • Experience in analytics in distributed computing environment
  • What's in it for you?

    A great chance to join a business with big growth aspirations. We are a fun, energetic, adaptable and professional team who love what we do.

    If you want a progressing career in big data space, then apply today!

    Only applicants meeting the strict criteria outlined above will be contacted as part of the shortlisting process.

    A bit about our Analytics Development Team

    The Analytic Development team build predictive models and attributes using Equifax's data assets in a distributed computing big data environment.

    These cover the consumer and commercial credit lifecycle, geodemographic and marketing attributes, credit ratings and fraud models, as well as any new areas where data driven decision making can be informed by predictive modelling.

    Full time

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