Entry / Junior Data Analyst
Liga de Empreendedorismo FGValley
Sydney, New South Wales, Australia (Hybrid) · ಅರೆಕಾಲಿಕ
ಅರ್ಜಿ ಸಲ್ಲಿಸುವವರಲ್ಲಿ ಮೊದಲಿಗರಾಗಿರಿ
- ಅನುಭವ
- ಯಾವುದೇ
- ಸಂಬಳ
- —
- ತೆರೆಯುವಿಕೆಗಳು
- 1
- ಪೋಸ್ಟ್ ಮಾಡಲಾಗಿದೆ
- 2 ಗಂಟೆಗಳ ಹಿಂದೆ
- ಕೆಲಸದ ಮೋಡ್
- ಹೈಬ್ರಿಡ್
- ವಿದ್ಯಾಭ್ಯಾಸ
- Data Analytics, Statistics, Mathematics, Business, Computer Science, or related field
- ಅರ್ಹತೆ
- Candidates who are available for a part-time hybrid role in Sydney and have an interest in data analytics can apply. Students, recent graduates, or early-career applicants with relevant coursework in analytics, statistics, mathematics, business, computer science, or a related subject are suitable.
- ಪುನರಾರಂಭ
- ಅರ್ಜಿ ಸಲ್ಲಿಸಲು ಕಡ್ಡಾಯ
ನೀವು ಎಲ್ಲಿ ಕೆಲಸ ಮಾಡುತ್ತೀರಿ
ಕೆಲಸದ ವಿವರ
Role overview
This part-time entry-level Data Analyst opportunity with Liga de Empreendedorismo FGValley is based in Sydney, New South Wales. The position follows a hybrid setup, combining on-site attendance with flexible work-from-home arrangements.
What you will do
You will support the organization by gathering, preparing, and structuring data from both internal and external sources so it can be used for decision-making. The role includes carrying out basic statistical analysis, building reports and dashboards, and turning data patterns into clear insights for colleagues who may not have a technical background.
You will also assist with data modeling tasks, keep methods and results well documented, and work closely with other team members on projects that rely on data. A key part of the role is learning quickly, following existing analytical workflows, and helping improve the way data is handled across the organization.
Skills and qualifications
The ideal candidate should bring strong analytical ability and a working foundation in data analytics practices. A basic grasp of statistics, including descriptive measures and introductory inferential ideas, is important.
Experience or familiarity with spreadsheets and data tools such as Excel, Google Sheets, SQL, or business intelligence platforms is helpful. You should also be comfortable contributing to data structure and relationship planning as part of modeling work.
Clear communication is essential, as you will need to explain findings to both technical and non-technical audiences. Attention to detail, a focus on data accuracy, and the ability to manage time well in a part-time hybrid setting are also expected.
Background study or coursework in Data Analytics, Statistics, Mathematics, Business, Computer Science, or a related discipline would be an advantage.