Additional office locations

Sydney

Job ID

21249

Date

19-Mar-2026

Permanent - Full time,

Job category

BFS - Data Scientist

• 5+ years of enterprise experience as a Data Scientist, delivering both predictive and Generative AI use cases through to production and a post-graduate degree (Masters or PhD) in a quantitative discipline such as Computer Science, Statistics, Engineering, or Mathematics is highly desirable. Ideally, you'd have a solid understanding of AI Risk and Governance principles
• Proven track record of mentoring and growing junior data scientists including establishing technical standards, conducting rigorous code/model reviews, and fostering a culture of continuous learning and high performance
• Experience and enthusiasm for Generative AI, including hands-on experience with prompt engineering, evaluation practices, agentic coding, AI-driven software engineering, and tools like the Agent Development Kit
• Proven experience in engineering features from large, complex datasets and schemas and proficiency in SQL is expected, with hands-on experience in BigQuery or other major SQL-based data warehouses
• Demonstrable proficiency in Python and its scientific computing ecosystem. You should have extensive experience with libraries for data manipulation and machine learning, such as scikit-learn, pandas, transformers/Hugging Face, and deep learning frameworks like PyTorch or TensorFlow
• Deep, hands-on expertise in MLOps and the end-to-end machine learning lifecycle. Highly capable designing scalable deployment architectures - such as AutoML workbenches like DataRobot or the ML stack of a major cloud provider, such as GCP Vertex AI, AWS SageMaker, or Azure AI Studio
• In addition to your core skillset, we highly value your adjacent abilities, particularly around data analytics, telling stories with data, working within large engineering teams, MLOps and CI/CD, product thinking, and a strong general understanding of software development best-practices like code version control (e.g. git), end-to-end data workflow development and automation (e.g. Dataform, Control-M) and CI/CD.
• 5+ years of enterprise experience as a Data Scientist, delivering both predictive and Generative AI use cases through to production and a post-graduate degree (Masters or PhD) in a quantitative discipline such as Computer Science, Statistics, Engineering, or Mathematics is highly desirable. Ideally, you'd have a solid understanding of AI Risk and Governance principles
• Proven track record of mentoring and growing junior data scientists including establishing technical standards, conducting rigorous code/model reviews, and fostering a culture of continuous learning and high performance
• Experience and enthusiasm for Generative AI, including hands-on experience with prompt engineering, evaluation practices, agentic coding, AI-driven software engineering, and tools like the Agent Development Kit
• Proven experience in engineering features from large, complex datasets and schemas and proficiency in SQL is expected, with hands-on experience in BigQuery or other major SQL-based data warehouses
• Demonstrable proficiency in Python and its scientific computing ecosystem. You should have extensive experience with libraries for data manipulation and machine learning, such as scikit-learn, pandas, transformers/Hugging Face, and deep learning frameworks like PyTorch or TensorFlow
• Deep, hands-on expertise in MLOps and the end-to-end machine learning lifecycle. Highly capable designing scalable deployment architectures - such as AutoML workbenches like DataRobot or the ML stack of a major cloud provider, such as GCP Vertex AI, AWS SageMaker, or Azure AI Studio
• In addition to your core skillset, we highly value your adjacent abilities, particularly around data analytics, telling stories with data, working within large engineering teams, MLOps and CI/CD, product thinking, and a strong general understanding of software development best-practices like code version control (e.g. git), end-to-end data workflow development and automation (e.g. Dataform, Control-M) and CI/CD.