Mid-Level Data Scientist

MLOps/AWS

Sydney – Hybrid

$170k + Super

Our client, in the lending space, are looking for a skilled Data Scientist from a lending/credit risk/modelling or insurance environment who will support the whole end-to-end model lifecycle from ideation to deployment and (if necessary) building and deploying Gen AI/ML applications for the business to serve themselves insights/ predictions, tackling a variety of use cases such as chatbots, text-to-SQL solutions, and multi-agent systems to improve business processes.

This role supports the development of models, tools, and applications to drive business strategy and profitability. Responsibilities span the full ML lifecycle—from model building to deployment—using technologies like Python, DataRobot, Snowflake, and Streamlit. The role also involves close collaboration with business teams.

In addition, the role drives the team’s Generative AI efforts (e.g. chatbots, text-to-SQL, multi-agent systems) and shapes the ML Ops and emerging LLM Ops vision. This includes building scalable infrastructure, automating pipelines, setting up CI/CD, containers (Kubernetes) experiment tracking, and version control.

Ideal candidate profile:

· Expert in Python and end-to-end modeling

· Experience with Azure AI Foundry, CoPilot Studio, MLFlow, Kubernetes

· Background in ML Ops software engineering

· Skilled in cloud-native tools (Snowflake/Snowpark, Azure, AWS)

· Bonus: Experience with Streamlit or Azure web apps

If this opportunity speaks to you, please submit a relevant and aligned CV through the portal attached.