Data Analyst (Entry/Junior)
Melbourne, Victoria, Australia (Hybrid) · ഭാഗിക സമയം
അപേക്ഷിക്കുന്ന ആദ്യയാളാകൂ
- അനുഭവം
- ഏതെങ്കിലും
- ശമ്പളം
- —
- ഓപ്പണിംഗുകൾ
- 1
- പോസ്റ്റ് ചെയ്തു
- 2 മണിക്കൂർ മുമ്പ്
- പ്രവർത്തന രീതി
- ഹൈബ്രിഡ്
- പുനരാരംഭിക്കുക
- അപേക്ഷിക്കാൻ നിർബന്ധം
നിങ്ങൾ എവിടെ ജോലി ചെയ്യും
ജോലി വിവരണം
Role Overview
This part-time Data Analyst (Entry/Junior level) position is based in Melbourne, Victoria, combining on-site and remote work. The analyst will contribute by gathering, cleaning, and analyzing data linked to organizational campaigns, advocacy initiatives, and community engagement. Duties involve assembling datasets from diverse sources, performing fundamental statistical analyses, constructing straightforward data models, and converting data insights into easy-to-understand reports and dashboards for decision-makers who may not have technical backgrounds.
Key Responsibilities
The analyst will work closely with campaign teams to define essential performance indicators, continuously monitor outcomes, and support the enhancement of data accuracy and record keeping. This role provides meaningful hands-on experience in social impact analytics within a supportive and educational workplace.
Candidate Qualifications
- Must have strong analytical abilities and basic capabilities in data analytics to interpret and derive insights from data.
- Should understand fundamental concepts in statistics and data modeling to assist in quantitative evaluations and simple predictive analysis.
- Effective communication skills are essential for explaining data results to a variety of audiences and collaborating with multiple teams.
- Proficiency with spreadsheet software such as Excel or Google Sheets, along with introductory skills in data visualization platforms like Tableau or Power BI, is required.
- Interest in social justice, reproductive rights, or advocacy is important, as well as the ability to work responsibly in a hybrid Melbourne setting.
- Preferred qualifications include academic coursework or degrees in Data Science, Statistics, Economics, Public Policy, or related disciplines, along with basic knowledge of programming or data query languages such as Python, R, or SQL.