AI Data Scientist — LLMs, Production ML & Client Impact

ATNIS Pty Ltd; Sydney; On-site; AUD 147,000 - 150,000; Full time

Job summary

ATNIS Pty Ltd, a Sydney-based technology consultancy, seeks an experienced Data Scientist to lead AI initiatives and support client engagements across cybersecurity, cloud and network infrastructure. The role covers the full analytics lifecycle, from framing problems to deploying models in production.

The successful candidate will design, train and evaluate ML models, build data pipelines on Azure/Databricks, and communicate results to technical and non-technical stakeholders while ensuring

Qualifications

• A degree in data science, computer science, statistics, mathematics, engineering or a related quantitative discipline (postgraduate qualification advantageous).
• At least two years of commercial experience delivering data science or machine learning solutions into production.
• Demonstrated experience building large language model solutions, including retrieval-augmented generation, embeddings and agent-based workflows.

Responsibilities

• Design, build and run AI/ML solutions to improve service delivery and client offerings.
• Support client engagements in cybersecurity, cloud and network infrastructure data science projects.
• Create dashboards and visualisations; prepare reports and presentations for clients and internal stakeholders.
• Apply data governance, privacy and security practices to all data handled.
• Document methods, code and results and contribute to analytic standards.

Skills

Problem-solving

Attention to detail

Independent work

Teamwork

Education

Data science / CS / statistics / maths / engineering degree

Tools

Python

SQL

Azure

Databricks

Power BI

Job description

ATNIS Pty Ltd, a Sydney-based technology consultancy, seeks an experienced Data Scientist to lead AI initiatives and support client engagements across cybersecurity, cloud and network infrastructure. The role covers the full analytics lifecycle, from framing problems to deploying models in production.

The successful candidate will design, train and evaluate ML models, build data pipelines on Azure/Databricks, and communicate results to technical and non-technical stakeholders while ensuring