Data Scientist

Role overview

We are looking for a Data Scientist to join a global financial services business in Sydney as part of an AI and Risk Analytics function. This is a permanent position with a salary range of $160,000 to $180,000. The role focuses on delivering enterprise-grade AI and machine learning solutions that improve how risk teams work, with an emphasis on moving ideas from experimentation into live production systems.

You will work closely with engineering, data engineering and business teams to create solutions that are scalable, dependable and aligned with governance expectations. The position suits someone who enjoys building practical data science products that deliver measurable impact across business and risk management operations.

What you'll do

• Develop, implement and enhance machine learning and AI solutions for complex business problems.
• Use Python and SQL to create strong data science models across large and varied datasets.
• Partner with engineering teams to take models into production and connect them to enterprise platforms.
• Track model results, spot opportunities to improve performance and support ongoing tuning.
• Create prototypes and proof-of-concepts for new AI ideas, including relevant Generative AI use cases.
• Apply suitable governance, documentation and risk controls throughout the solution lifecycle.
• Share technical insights and recommendations with both technical and non-technical audiences.

What we're looking for

The ideal candidate will bring hands-on data science experience along with a strong delivery mindset. You should be comfortable working on solutions that go beyond analysis and are actually deployed into production environments.

• Proven experience delivering machine learning or advanced analytics solutions into production.
• Advanced ability in Python and SQL.
• Experience handling large, complex datasets and building scalable analytical approaches.
• Familiarity with software engineering practices such as Git, version control and CI/CD processes.
• Good understanding of statistical modelling, machine learning methods and model assessment.
• Experience working alongside engineers to deploy and maintain production solutions.
• Awareness of data governance, model risk, compliance and enterprise delivery requirements.
• Strong communication skills with the ability to work effectively with both technical and business stakeholders.

Nice to have

• Exposure to Generative AI or Large Language Models.
• Experience with Natural Language Processing.
• Knowledge of Retrieval-Augmented Generation.
• Experience using cloud platforms such as Azure, AWS or GCP.
• Familiarity with Databricks, MLflow or similar MLOps tools.
• Background in banking, financial services, insurance or another regulated environment.

Additional information

This is a permanent, full-time, onsite role based in Sydney, New South Wales, Australia.

No application deadline, start date, duration, or vacancy count was specified in the source.