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Data Analyst Jobs in Australia

Description

Gathers, cleans and interprets data by processing and applying information technology tools to transform, prepare and communicate results using interactive visualisations such as graphs and charts.

Skill Level: 1

Unit Group 2241: Mathematical Science Professionals

Mathematical Science Professionals develop and apply actuarial, mathematical, statistical and quantitative principles and techniques to solve problems in a range of fields such as business and finance, scientific and social research, and engineering. Econometricians are excluded from this unit group.

Econometricians are included in Unit Group 2243 Economists.

Indicative Skill Level:

In Australia and New Zealand:

Most occupations in this unit group have a level of skill commensurate with a bachelor degree or higher qualification. In some instances relevant experience and/or on-the-job training may be required in addition to the formal qualification (ANZSCO Skill Level 1).

Registration or licensing may be required.

Tasks Include:

  • defining, analysing and solving complex financial and business problems relating to areas such as insurance premiums, annuities, superannuation funds, pensions and dividends
  • examining financial projections for general insurance companies, finance companies, government and other organisations
  • designing new types of policies, assessing risks and analysing investments in life insurance, superannuation funds, health insurance, friendly societies, financial markets and other areas
  • formulating mathematical models to simulate processes
  • applying models to experimental observations, and adjusting and recasting the models
  • using numerical analysis methods to develop algorithms and perform computations
  • liaising with management and clients to determine the subject or area to be surveyed or examined
  • specifying the data to be collected, and the methodology to be used in collection and analysis
  • evaluating and describing the reliability and utility of source information
  • analysing and interpreting data, and producing relevant statistics to describe and infer particular trends and patterns
  • data mining and data cleansing to discover trends to extract insight
  • building and deploying machine learning frameworks

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