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Entry-Level Data Analyst

Nomi Trading and Logistic Services

Melbourne, Victoria, Australia (Hybrid) · Paruh Waktu

Jadilah yang pertama mendaftar

Pengalaman
Setiap
Gaji
Lowongan
1
Diposting
3 jam yang lalu
Mode kerja
Hibrida
Pendidikan
Progress toward or completion of degree in Data Science, Statistics, Mathematics, Business, or related field
Melanjutkan
Wajib mendaftar

Tempat Anda akan bekerja

Deskripsi pekerjaan

Role Overview

This part-time Data Analyst position, located in Melbourne, VIC, offers a hybrid work environment combining onsite presence with flexible work-from-home days. The primary focus is on gathering, cleansing, and organizing operational and logistics data from various sources to enhance reporting and performance measurement.

Key Responsibilities

  • Create and maintain basic dashboards to visualize data effectively.
  • Generate periodic summaries of data to support monitoring efforts.
  • Assist with data modeling activities aimed at improving forecasting accuracy and optimizing logistics resources.
  • Conduct exploratory data analysis to detect patterns, trends, and operational inefficiencies.
  • Prepare clear documentation of findings and present actionable insights to internal teams.
  • Collaborate closely with operations, finance, and management departments to ensure integrity and usefulness of data.

Candidate Profile & Qualifications

  • Strong analytical thinking combined with fundamental data analytics competencies to interpret business and operational datasets.
  • Foundational knowledge of statistics to support quantitative assessment and performance tracking.
  • Basic experience or understanding of data modeling techniques for forecasting and logistics optimization.
  • Effective communication skills essential for sharing insights and working across different teams.
  • Familiarity with spreadsheet software such as Excel or Google Sheets; experience with data visualization or BI tools is a plus.
  • Preferred candidates will have completed or be pursuing a degree in Data Science, Statistics, Mathematics, Business, or related disciplines.
  • Ability to work independently while managing time efficiently in a part-time schedule, with strong attention to detail in handling data tasks.

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