Senior Data Scientist

Shift

. Build and deploy machine learning models predicting credit risk, including PD, LGD, EAD and expected loss .

Posted 11/9/2026full-timeSydney • AustraliaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying machine learning models for credit risk prediction, with a strong foundation in Python and SQL. Proven ability to lead projects, collaborate across teams, and communicate complex concepts to stakeholders.

Highest-signal resume keywords

Machine Learning Model DevelopmentPredictive ModelingPython ProgrammingSQL ProficiencyModel Deployment and Monitoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive ModelingMachine LearningStatistical AnalysisData ValidationVersion ControlCI/CDAPI DevelopmentModel MonitoringConfidence MeasurementAutomated Decision Making

Soft Skills

CollaborationCommunicationKnowledge SharingCuriosity

Tools & Technologies

DatabricksDistributed Computing Environment

Industry Keywords

Credit RiskFinancial ServicesLending

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Build and deploy machine learning models predicting credit risk, including PD, LGD, EAD and expected loss
Model how different types of security change loss exposure
Make the prototype model deployment layer scalable, versioned, monitored and reliable for automated decisions
Ensure production models have monitoring, data validation and documentation
Incorporate new data sources, including insights from the AI-powered Customer Knowledge Engine
Lead projects from start to finish
Share knowledge and raise the team’s engineering standards
Collaborate with Credit, Product, Risk and Technology teams
Agree model deliverables and explain results in plain language

Requirements

What you’ll need

5+ years building predictive models in a business setting
Track record of getting predictive models into production and maintaining them
Strong Python and SQL skills
Version control, CI/CD, testing and code review experience
Hands-on experience building model services or APIs, including serving, versioning and monitoring
Experience with Databricks or another distributed computing environment
Solid statistical foundation, including measuring confidence in model predictions
Ability to explain complex work simply to senior stakeholders
Curiosity about using AI to work smarter
Experience in credit risk, lending or financial services is a plus, but not essential
Legal right to work in Australia or New Zealand without employer sponsorship

Benefits

Comp & perks

Hybrid working policy with state-based workplaces
Up to 26 weeks paid parental leave
Strategy Week twice a year
Fortnightly all-company business updates
Flat structure with opportunities to learn from senior leaders
Wellbeing benefits supporting physical, psychological and financial wellbeing
Birthday day off
End-of-trip facilities