Data Analytics

Location: Melbourne, VIC

Duration: 5-6 months (start date August 2017)

PLEASE NOTE applicants must have current enrolment status for the entire duration of the internship. Students submitting their thesis during or prior to the start date may not be shortlisted. If unsure about your enrolment status please contact the Business Development adviser.

Skills required

The successful candidate will have:

  • Exposure within data analytics
  • Have a general understanding of financial institutions and financial models
  • Experience working with large data sets, statistical techniques and analysis such as data mining, regression, clustering and segmentation

Currently completing their PhD (Please note: PhD students must be in their final year of study during the expected start date of the internship)

Project Background

ANZ operate in 34 markets globally with representation in Australia, New Zealand, Asia, Pacific, Europe, America and the Middle East. ANZ is among the top 4 banks in Australia, the largest banking group in New Zealand and Pacific, and among the top 50 banks in the world.

ANZ’s Advanced Analytics team is accountable for contributing to the development and delivery of analytical insights which result in business action that has a positive impact to ANZ’s financial standing, customer satisfaction levels and/or competitive advantage. The Advanced Analytics team is tasked with balancing business insight, acumen and analytics to develop insights that informs business thinking and develops intellectual property to move the business forward.

The Advanced Analytics team requires an intern to analyse and present data in a manner that tells compelling stories that stimulate behaviour change from key decision makers within ANZ. Research will include, but is not limited to:

  • Strategic and Tactical Analytics
  • Marketing Analytics
  • Regression Modelling
  • Business Analytics
  • Segmentation
  • Customer Behaviour Analytics
  • Experimental Design
  • Trigger Design and Development
  • Undertaking both proactive and reactive analysis across large sets of financial, customer and economic data and present back to the business new and highly valuable insights
  • Adherence to ‘Best-in-Class’ process, procedure and governance

Research to be conducted

This position is suited for current students studying business analytics, data science, mathematics, economics and/or computer science.

Based on skills, students will be assigned to complete selected Advanced Analytics project based work items to acquire hands on experience building our customer analytic model assets.

Examples of the research projects to be undertaken, using SAS/R and multiple databases include:

Building predictive models to improve marketing sales offerings and return on investments, such as;

  • The use of statistical modelling techniques to identify customers with a high propensity to respond to a personal loans campaigns using customer demographics and current credit card behaviour (utilisation, spend categories etc.)
  • Use of refinance and Home Loan data to identify customers with a propensity to refinance a Home Loan elsewhere with the aim to improve customer relations and retain customers
  • Undertaking business analytics with multiple databases to improve business outcomes & customer experience such as;
  • Use of customer profiling and segmentation methodologies for tracking and analysis of web pages visited or timely offers to existing customers and/or sizing opportunity through analysis of relevant offers, incentives and lead time requirements.
  • Use of SAS/R and multiple data tables for analysis of high usage customers to identify causation, process change requirements and alternative channel solutions e.g. SMS alerts and/or quantify impact of channel migration strategies.

Interns will be partnered with a senior ANZ Analytics team member who will provide line management, sponsorship, coaching and domain expertise.

This is an opportunity to put to practice your analytics skills alongside experienced data scientists in a global institution. The intern will gain experience in:

  • Developing advanced and complex predictive models using software tools.
  • Ability to interpret and evaluate the outcomes
  • Work with large and diverse data sets in building, validating and using predictive tools
  • Increase knowledge of financial institution data, strategy & products
  • Use of tools and techniques to enable provision of analytics to support business cases, hypotheses and opportunity analysis

Additional details

The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.

It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 50% of their time on-site with the industry partner. The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.

The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.

To participate in the AMSI Intern program, all applicants must satisfy the following criteria:

  • Be a PhD student currently enrolled at an AMSI member institution.
  • PhD candidature must be confirmed.
  • Applicants must have the written approval of their Principal Supervisor to undertake the internship. This approval must be submitted at the time of application.
  • Students must be in or nearing their final year of study.
  • Internships are also subject to any requirements stipulated by the student’s and the academic mentor’s university.
Applications Close

26 July 2017

Reference:
INT – 0330