About the role:
As a Data Scientist at Shift, you won't just be building models, you'll be shaping how we understand credit risk, fraud and profitability. From hands on Python development to deep dives into machine learning and credit strategy, you'll be right at the centre of solving complex problems that directly impact the business. You'll collaborate with smart, curious people across teams and you'll get space to grow your technical skills while contributing to innovative, high‐impact projects.
What you'll do:
* Develop and validate models for Credit risk (PD, LGD, EAD), provisioning (AASB/IFRS9), servicing, fraud and profitability using traditional ML, Bayesian modelling, and neural networks
* Advanced data wrangling, working with complex and unstructured datasets
* Contribute to model evaluation, monitoring and governance for internal and regulatory stakeholders
* Take models from development to deployment in production using ML engineering tools
* Optimise credit strategy through modelling, automation, and performance insights
* Research new modelling methodologies and challenge the status quo to drive innovation
* Work with diverse data sources (e.g. bank statements, credit bureaux, OCR) and ensure data integrity
* Share your knowledge through team discussions, workshops and informal peer sessions
* Collaborate with business and technology teams to align data science with business goals
What you'll bring:
* Demonstrated experience coding in Python and SQL
* Solid quantitative background – you're comfortable with stats, modelling, and problem solving
* Experience building statistical models including data wrangling, feature engineering, and model evaluation.
* Experience in Databricks, PySpark, or similar clustered computing environments
* Experience deploying ML models using MLFlow or other ML engineering tools in production
* Excellent communication skills – you can explain complex models to non-technical teams
* Ability to manage projects, define scopes, and deliver aligned outcomes
* Collaborative mindset with curiosity and a passion for learning
* Commercial or financial services background
* Master's or PhD in a quantitative discipline (Stats, Maths, CS, Engineering, etc.)
Key benefits:
* Collaborative teams – a flat structure means everyone can learn from colleagues and senior leaders around the business.
* Be involved – come together with all of your colleagues every 100 days to share the product and technology roadmap and business strategy.
* Flexible working environment – we're headquartered in North Sydney with state-based workplaces and offer a flexible work policy.
* Family support – industry leading 26 weeks paid parental leave.
* Purpose built spaces within our office – designed for collaboration, brainstorming, socialising, and focused work.
* Range of benefits supporting your physical, psychological and financial wellbeing. From a day off on your birthday to excellent end of trip facilities.
#J-18808-Ljbffr