Data Scientist | AI & Risk Analytics
Sydney
Permanent
$160-180k
We're partnering with a leading global financial services organisation to appoint a Data Scientist to join a high-performing AI and Risk Analytics team. This is an opportunity to work on enterprise-scale AI initiatives that are transforming the way risk teams operate, leveraging machine learning and advanced analytics to solve complex business problems.
This role is ideal for someone who enjoys taking data science solutions beyond experimentation and into production, working closely with engineering teams to deliver scalable, reliable and well-governed AI capabilities.
As a Data Scientist, you'll play a hands-on role in developing, deploying and continuously improving machine learning and AI solutions that support critical business and risk management functions. You'll collaborate with cross-functional teams including data engineers, software engineers and business stakeholders to ensure models are production-ready, measurable and aligned with governance standards.
This is a highly collaborative position where you'll contribute across the full data science lifecycle-from problem definition and experimentation through to deployment, monitoring and optimisation.
Design, develop and deploy machine learning and AI solutions that address complex business challenges.
Build robust data science models using Python and SQL across large and diverse datasets.
Work closely with engineering teams to productionise models and integrate solutions into enterprise platforms.
Monitor model performance, identify opportunities for improvement and support ongoing optimisation.
Develop proof of concepts and prototype new AI capabilities, including emerging Generative AI technologies where appropriate.
Ensure solutions are developed with appropriate governance, documentation and risk controls.
Present technical findings and recommendations to both technical and non-technical stakeholders.
You'll be an experienced Data Scientist who combines strong technical capability with a practical mindset and enjoys delivering solutions that create measurable business value.
You'll ideally bring:
Commercial experience delivering machine learning or advanced analytics solutions into production environments.
Strong programming skills in Python together with advanced SQL capability.
Experience working with large, complex datasets and building scalable analytical solutions.
Exposure to software engineering practices including Git, version control and CI/CD workflows.
A solid understanding of statistical modelling, machine learning techniques and model evaluation.
Experience working alongside engineering teams to deploy and support production solutions.
An appreciation for data governance, model risk, compliance and enterprise delivery standards.
Excellent communication skills with the ability to engage technical and business stakeholders.
Experience with any of the following will be advantageous:
Generative AI or Large Language Models (LLMs)
Natural Language Processing (NLP)
Retrieval-Augmented Generation (RAG)
Cloud platforms (Azure, AWS or GCP)
Databricks, MLflow or modern MLOps tooling
Banking, financial services, insurance or other highly regulated industries
If this is of interest get in touch:
