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Senior Data Scientist - Credit Risk

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Onsite

Senior Data Scientist - Credit Risk

Preacta Recruitment

Senior Data Scientist - Credit Risk

Skills

SQL QueriesPythonData ScienceRGitData AnalysisMachine LearningAI

19 days ago

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Important information


Contract type:

Permanent

Location:

Sydney NSW, Australia

Work mode:

Onsite

Published on:

20 October 2026

What they need


Senior Data Scientist, Credit Risk (ECL and IFRS 9)

Sydney | Hybrid, 3 days in office | $200k + super + bonus

The company
This is a well-established Australian lender with a large, data-rich loan book. The data and AI function is growing, with ML and data engineers working alongside the credit risk analytics team. That means your models get built and deployed properly, not left in a spreadsheet. You get the scale and data depth of a mature lender without big bank bureaucracy.

The role
This is a senior individual contributor role with no direct reports. You’ll sit within the credit risk analytics team.

ECL is the core of the job. You’ll build, calibrate and monitor IFRS 9 impairment models across PD, LGD, EAD, staging, overlays and macroeconomic scenarios. You’ll run sensitivity analysis and back-testing. When provisioning moves, you’ll be the one explaining why to Finance. Your work needs to hold up in front of auditors and model validation.

Beyond ECL, you’ll work on scorecards, behavioural models and segmentation. You’ll also track portfolio performance across arrears, losses, hardship and vintages, and support credit policy and risk appetite decisions with solid analysis. You’ll work with engineers to get models into production cleanly, and help lift the team’s standards through peer review.

What you’ll need

  • 5+ years in data science, credit risk modelling or portfolio analytics in lending or financial services
  • Hands-on experience building, calibrating or monitoring ECL models under IFRS 9
  • Scorecard, behavioural or segmentation modelling experience
  • Strong SQL plus Python, R or SAS
  • Version control, testing and reproducible workflows on a modern data platform
  • Clear model documentation and comfort with audit and validation scrutiny
  • A degree in statistics, maths, economics, actuarial science or another quantitative field (postgrad a plus)

Nice to have: consumer or secured lending experience, and a working knowledge of Australian responsible lending and financial reporting requirements.
Apply now or reach out directly for a confidential chat.

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