Remote Data Science Intern: Build ML & Analytics in Sydney

Remote Data Science Intern: Build ML & Analytics in Sydney

Sydney Internship 50715 - 61985 $ / year (est.) Remote
B

At a Glance

  • Tasks: Transform large datasets into insights and build ML models for impactful analytics.
  • Company: Bright Network Consulting, a forward-thinking firm embracing remote work.
  • Benefits: Gain hands-on experience, flexible hours, and mentorship from industry experts.
  • Other info: Collaborate with a dynamic team and enhance your data science skills.
  • Why this job: Make data-driven decisions that shape business strategies while working remotely.
  • Qualifications: Strong foundation in statistics, problem-solving, and familiarity with Python and SQL.

The predicted salary is between 50715 - 61985 $ per year.

Bright Network Consulting seeks a Data Scientist for a fully remote role based in Australia.

You will transform large datasets into actionable insights, build ML models, and deliver business-ready analytics.

You will work with Python, SQL, and visualization tools (Power BI/Tableau) to drive data-driven decisions across teams.

A strong foundation in statistics and problem-solving is essential for success. Collaborate with data engineers, analysts and developers; monitor model performance and

Remote Data Science Intern: Build ML & Analytics in Sydney employer: Bright Network Consulting

Bright Network Consulting offers a dynamic work environment with fully remote roles, allowing employees to collaborate across various teams and disciplines. The company emphasizes professional growth through hands-on experience in cutting-edge fields such as cyber security and data analytics. Employees benefit from the opportunity to work with modern technologies and contribute to impactful projects.

B

Contact Details:

Bright Network Consulting Recruitment Team

We think you need these skills to ace Remote Data Science Intern: Build ML & Analytics in Sydney

Data Analysis
Machine Learning
Python
SQL
Power BI
Tableau
Statistical Analysis