Data Analyst Career Opportunity

3 days ago

Darwin, Northern Territory, Australia beBeeData Full time $80,000 - $100,000
Data Analyst Career Opportunity

This role is an excellent chance to build a successful career in data analysis and contribute to the development of policies and programs that shape Australia's workforce and skill needs.

As a data analyst, you will apply your analytical skills to inform evidence-based policy decisions, working closely with experienced supervisors to learn industry-standard software. You will be responsible for developing skills in quantitative data analysis using SAS, R, Python, Power BI, and SQL, and will work on various projects including data collection and management, performance reporting and program evaluation, compliance and assurance, and economics.

You will benefit from the department's Data Analyst Network, an online forum for data analysts to share information and skills. This network provides valuable opportunities for professional growth and development, enabling you to stay up-to-date with the latest trends and best practices in data analysis.

To succeed in this role, you should have strong analytical and communication skills, be highly motivated, and have a good work ethic. Experience with programming languages is beneficial but not essential. We are looking for graduates from a wide range of disciplines who want to play a part in shaping Australia's future and informing the decision-making process.

Key Responsibilities:

  • Apply analytical skills to inform evidence-based policy decisions
  • Develop skills in quantitative data analysis using industry-standard software
  • Work on various projects, including data collection and management, performance reporting and program evaluation, compliance and assurance, and economics
  • Benefit from the department's Data Analyst Network
  • Contribute to the development of policies and programs that contribute to Australia's workforce and skill needs

What You Will Learn:

  • Quantitative data analysis using industry-standard software
  • Programming languages, including Python and R
  • Data collection and management best practices
  • Performance reporting and program evaluation methodologies
  • Economics and budget analysis techniques
  • Geospatial analysis and machine learning methods

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