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Your Money Home Loans

Data Scientist / ML Builder (Early Career)

Your Money Home Loans

Brisbane, Queensland, Australia · Contrato

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Experiência
Qualquer
Salário
Vagas
1
Publicado
há 3 semanas
Modo de trabalho
No escritório
Educação
Data Science, ML, Statistics, Applied Maths, or Computer Science
Elegibilidade
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.
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Onde você trabalhará

Descrição da vaga

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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