Data Scientist - Financial Forecasting (Large retail)

Location: Brisbane

Engagement: Contract - 3 months initially + another 3 months

My client, a leading technology consultancy, is kicking off a large-scale project within the retail industry. They are looking for a Data Scientist who specialises in financial data, statistical machine learning, and forecasting models.

This role is focused on analytical, statistical modelling and not GenAI.

What You’ll Do

• Analyse very large financial datasets and perform deep EDA to uncover patterns and drivers.
• Build, compare, and refine forecasting models (ARIMA, Prophet, XGBoost, LSTM).
• Develop features, test hypotheses, and continually improve model performance.
• Validate ML outputs against rule-based or business logic forecasts.
• Work within the Databricks ML environment, using MLflow for tracking and experiment management.
• Communicate insights clearly to technical and non-technical stakeholders.

What We’re Looking For

• Strong skills in Python, PySpark, SQL, and ML libraries (pandas, scikit-learn, statsmodels, Prophet).
• Experience with time-series forecasting and financial or retail datasets.
• Skilled in feature engineering, EDA, model validation, and error analysis.
• Comfortable with large-scale datasets, reproducible notebooks, and optimisation.
• Curious, analytical mindset with strong communication and documentation skills.
• Ability to collaborate with Finance, Data Engineering, and BI teams.

If you’re a data scientist who thrives in analytical environments and loves working with complex financial data, we’d love to hear from you.