ഗ
Entry-Level Data Analyst
Sydney, New South Wales, Australia (Hybrid) · ഭാഗിക സമയം
അപേക്ഷിക്കുന്ന ആദ്യയാളാകൂ
- അനുഭവം
- ഏതെങ്കിലും
- ശമ്പളം
- —
- ഓപ്പണിംഗുകൾ
- 1
- പോസ്റ്റ് ചെയ്തു
- 21 മണിക്കൂർ മുൻപ്
- പ്രവർത്തന രീതി
- ഹൈബ്രിഡ്
- വിദ്യാഭ്യാസം
- Degree in Data Science, Statistics, Mathematics, Computer Science or related quantitative field preferred
- പുനരാരംഭിക്കുക
- അപേക്ഷിക്കാൻ നിർബന്ധം
നിങ്ങൾ എവിടെ ജോലി ചെയ്യും
ജോലി വിവരണം
Role Overview
This part-time Data Analyst position is based in Sydney, NSW, offering a hybrid work model that blends on-site collaboration with the flexibility to work remotely. The role focuses on supporting AI-driven product enhancements and internal business decisions by managing data activities.
Primary Responsibilities
- Collect, clean, and organize datasets to support AI applications and business insights.
- Perform basic data analyses and create visualizations and dashboards for clearer data interpretation.
- Assist in data modeling efforts under supervision of senior team members.
- Document analysis results and prepare comprehensive reports.
- Effectively communicate findings to a range of stakeholders, both technical and non-technical.
- Coordinate closely with engineering, product, and operations teams to ensure data integrity and relevance to business objectives.
Candidate Requirements
- Possess strong analytical capabilities with foundational knowledge in data analytics and statistics.
- Understand data modeling principles and experience working with structured data.
- Exhibit clear written and spoken communication skills to explain data insights effectively.
- Familiar with tools like Excel, SQL, Python or R, and visualization software such as Tableau or Power BI is advantageous.
- Preferably has academic background in quantitative disciplines such as Data Science, Statistics, Mathematics, or Computer Science.
- Show attention to detail, a keen interest in data, and eagerness to develop skills in a fast-evolving AI environment.
- Capable of excelling in a hybrid work environment with both in-person and remote teamwork.