Advanced Analytics Professional

1 week ago

Melbourne, Victoria, Australia beBeeDataScientist Full time $50,000 - $75,000

Data Scientist Role

We are seeking a skilled and analytical Data Scientist to join our team.

Job Description

This role presents an opportunity for emerging data professionals with strong technical capability to contribute to meaningful outcomes on a national scale. As a Data Scientist, you will support various reporting, analysis, and data management activities.

  • You will work with data from multiple sources, apply statistical and modelling techniques, and provide insights that inform decision-making and reporting at the highest levels.
Key Responsibilities:

The successful candidate will have solid technical expertise, strong problem-solving skills, and the ability to communicate complex analysis clearly to both technical and non-technical stakeholders.

  • Extract, cleanse, and prepare data from multiple sources (including data warehouses) and apply quality checks.
  • Undertake data analysis and contribute to the development of performance monitoring and reporting.
  • Apply statistical and mathematical modelling techniques to support forecasting, scenario testing, dashboards, and predictive modelling.
  • Communicate findings and progress clearly to team members and management.
  • Prepare technical reviews, commentary, tables, charts, and reporting for senior stakeholders.
  • Contribute to the continuous monitoring of outcomes, risks, and financial sustainability.
Required Skills and Qualifications

The ideal candidate will possess experience in data analytics, strong programming skills, and proficiency in SQL or SAS.

  • Experience in data analytics, ideally supporting policy, reporting, or decision-making.
  • Strong R or Python programming skills, including data manipulation and analysis.
  • Proficiency in SQL or SAS for data extraction and management.
  • Ability to work effectively in a team, with minimal supervision.
  • Well-developed written and verbal communication skills.
  • Familiarity with statistical modelling (e.g., GLM, gradient boosting, machine learning techniques).
  • Experience developing dashboards, visualisations, and reports for non-technical audiences.

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