Data Insights Specialist

6 days ago

Sydney, New South Wales, Australia beBeeData Full time $92,000 - $124,000

We are seeking a seasoned Data Insights Specialist to join our team. In this role, you will be responsible for turning complex data into actionable insights that drive business growth.

The successful candidate will possess strong analytical skills and experience working with large datasets. You will be expected to develop and maintain interactive dashboards using Power BI or Tableau, as well as provide data-driven insights to support business decisions.

Key Responsibilities:

  • Gather, clean, and analyze large datasets related to operations, workforce, and performance.
  • Develop and maintain dashboards and reports to monitor key performance indicators (KPIs) such as turnaround times, SLA adherence, and productivity metrics.
  • Provide insights to identify trends, inefficiencies, and opportunities for improvement.
  • Automate and streamline reporting processes to reduce manual effort and increase data accuracy.
  • Translate complex data into clear, actionable visualizations and reports for stakeholders.
  • Conduct trend analysis and provide data models to support business forecasting and planning.
  • Ensure data quality, consistency, and integrity across systems and reports.
  • Perform root cause analysis on operational issues using data insights.
  • Collaborate with internal teams to improve data structure, reporting accuracy, and availability.

Required Skills & Qualifications:

  • Proven experience as a Data Analyst, ideally in aviation, logistics, or operational environments.
  • Proficient in SQL, Excel, and BI tools such as Power BI or Tableau.
  • Strong analytical skills, with experience in statistical analysis and reporting.
  • Ability to work with large, complex datasets and relational databases.
  • Excellent communication skills and ability to present data-driven insights clearly.
  • Experience with workforce or operational planning data is a plus.
  • Knowledge of Python, R, or other statistical programming languages.
  • Experience in predictive analytics and/or machine learning techniques.
  • Understanding of on-time performance, turnaround metrics, or service level tracking in operational contexts.

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