Junior Data Analyst

TEAM is looking for a Junior Data Analyst to join our growing Data Science & Analytics team.

This is an opportunity to work across consulting and technology projects for organisations in mining, rail, utilities, and other asset-intensive industries.

You will work with experienced data professionals to explore complex datasets, uncover meaningful insights, and create analysis that helps clients make better decisions.

The data will not always be clean, complete, or perfectly documented. Your role will be to understand it, question it, and turn it into something useful.

What You Will Be Doing

You will contribute to client engagements from initial problem framing through to analysis and delivery, including:

Working with unfamiliar, incomplete, and inconsistent client datasets.Extracting, combining, and cleansing data using SQL and Python.Profiling data quality and identifying gaps, limitations, and anomalies.Turning broad business problems into clear analytical questions.Performing analysis that supports operational and commercial decisions.Building dashboards, visualisations, and reports for non-technical audiences.Contributing to client presentations and explaining your findings clearly.Creating repeatable, documented, and reproducible analytical processes.Supporting the development of reusable templates, tools, and analytics solutions.Managing your work against project timelines and budgets.Managing sensitive client information with care and confidentiality.

As your experience grows, you will progress towards owning smaller analysis workstreams and presenting your recommendations directly to clients.

What We Are Looking For

You may be a recent graduate or have up to approximately two years of relevant experience.

You Will Bring

A completed degree in engineering, data science, computer science, mathematics, statistics, economics, or another quantitative disciplinePractical SQL skills, including joins, filtering, and aggregations.Experience using Python for data analysis, ideally with pandas or Polars.The ability to write clear, reusable, and re-runnable code.Experience working with messy, incomplete, or complex data.Evidence that you can communicate analysis to a non-technical audience.Strong diligence and the instinct to investigate when something does not look right.Confidence working through ambiguity and changing priorities.A genuine interest in understanding the business problem behind the data.Willingness to occasionally travel to client sites.

Your communication experience could come from employment, university projects, a thesis, presentations, tutoring, student societies, or personal projects. We are interested in what you can demonstrate, not just the job titles you have held.

It would be a bonus if you have exposure to

Power BI or another visualisation platform.Git or other version-control tools.Databricks, Spark or similar data platforms.Machine learning, text analytics, or natural language processing.SAP or other enterprise systems.Mining, rail, utilities, or heavy industry.

Industry experience is not essential. We will help you build that knowledge on the job.

Why TEAM?

TEAM improves how critical assets are planned, maintained, and operated by bringing together asset-management expertise, data science, and practical technology.

You will join a business where data is central to how we solve client problems—not a support function sitting on the sidelines.

You Can Expect

Exposure to genuine client problems and operational datasets.Variety across industries, projects, and technologies.Support and coaching from experienced data and consulting professionals.The opportunity to build both technical and client-facing capability.Space to ask questions, evaluate ideas and contribute to how our analytics offering grows.A flexible Perth-based working environment.A clear pathway from completing defined analysis tasks to owning your own workstreams.

Interested?

Send us your CV and tell us about a piece of analysis you are proud of.

It could be from work, university, or a personal project. We would like to know what problem you were solving, what tools you used and what you discovered.

If you enjoy asking good questions, working through imperfect data, and turning analysis into action, we would like to hear from you.