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Your Money Home Loans

Data Scientist / ML Builder (Early Career)

Your Money Home Loans

Brisbane, Queensland, Australia · Vertrag

Bewerben Sie sich als Erste/r!

Erfahrung
Beliebig
Gehalt
Stellenangebote
1
Veröffentlicht
vor 6 Tagen
Work mode
Im Büro
Ausbildung
Data Science, ML, Statistics, Applied Maths, or Computer Science
Eligibility
Recent graduates and final-year students in Data Science, Machine Learning, Statistics, Applied Mathematics, or Computer Science who can work onsite in Brisbane and have at least one project to show.
Resume
Required to apply

Where you'll work

Stellenbeschreibung

Role overview

A small Brisbane-based financial services company is looking for an early-career data science and machine learning professional to help create a genuinely predictive layer over its current systems. The data is limited, messy, and drawn from real operations, so the work is commercially focused rather than academic. This is a practical, hands-on position where your contributions can influence how the business operates within a matter of weeks.

The team is especially interested in someone who can clearly distinguish real machine learning from simple if/then logic presented as AI.

What they are looking for

  • A recent graduate or final-year student in Data Science, Machine Learning, Statistics, Applied Mathematics, or Computer Science.
  • Strong Python ability, especially with pandas and scikit-learn, plus comfort working with databases.
  • Extra advantage if you have worked with LLMs and APIs.
  • Someone who has delivered at least one project, whether personal, academic, or otherwise, that handled messy real-world data.
  • Ability to explain technical ideas in straightforward business terms.
  • Confidence to advise when a problem does not truly require machine learning.

Application instructions

Applicants should share a link to a project, GitHub repository, or portfolio, and answer three short questions:

  • How does a system that you build actually learn?
  • What should happen when it encounters an edge case it has not seen before?
  • When would you recommend against using machine learning, and how would you determine that?

Additional information

This role is based in Brisbane, Queensland, Australia and is onsite. The business is a financial services company.

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