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Full timeTechnology

Senior Data Scientist

Ray WhiteSydney, Sydney🇦🇺AustraliaPosted 23 Oct 2026

Quick overview

SeniorityMid Senior
Employment typeFull Time
Work modeHybrid
LocationSydney, Sydney, Australia
SQLLLMPythondbtGenerative AIMachine LearningRAG

Job description

Duties and Responsibilities:

  • Design, develop, and implement AI and machine learning solutions to address complex business challenges.

  • Translate business problems into clear technical approaches, success measures and delivery plans.

  • Select appropriate approaches across generative AI, machine learning and statistical methods, balancing quality, complexity, cost and maintainability.

  • Establish evaluation frameworks, representative test datasets and automated checks to assess quality, reliability and business impact before and after release.

  • Work with Product, Engineering and Data Engineering to deliver scalable, maintainable AI solutions and integrate them into business products and workflows.

  • Guide the design of agentic workflows, including tool integration, access controls, failure handling and appropriate human review.

  • Establish and promote good practices for experimentation, testing, code review, documentation and responsible AI.

  • Communicate technical choices, trade-offs, limitations and recommendations clearly to stakeholders.

  • Mentor and guide junior data scientists to foster their growth and development.

  • Stay at the forefront of industry trends in AI, machine learning, and data science, driving innovation and continuous improvement within the team.

  • Communicate technical insights and recommendations effectively to both technical and non-technical stakeholders.


Skill and experience required:

  • A degree in Statistics, Computer Science, Data Science or a related quantitative field (Masters or PhD in Data Science will be an advantage)

  • 5+ years of hands-on experience in data science, including model development, deployment, and productionization.

  • Strong proficiency in Python and SQL for data manipulation, analysis, and machine learning model development.

  • Demonstrated experience delivering LLM applications, with practical knowledge of RAG, tool use and AI evaluation.

  • Strong foundations in statistics, machine learning and experimental design.

  • Experience deploying and operating solutions on cloud platforms and working with modern data infrastructure.

  • Proven ability to translate business problems into data science solutions and deliver impactful results.

  • Excellent communication and presentation skills with the ability to explain complex technical concepts to diverse audiences.

  • Experience mentoring others and improving technical practices within a team.

  • Experience delivering agentic AI workflows into production.

  • Experience with dbt or similar data transformation tools.

  • Experience applying AI in financial services or other environments involving sensitive data.


About the role:

As a Senior Data Scientist, you'll be a key contributor in our Data & Analytics team, leading the development and implementation of cutting-edge AI and ML solutions. You'll work closely with business stakeholders, data engineers, data modellers, software engineers and analysts to deliver impactful, data-driven outcomes. This is a high-impact role where you'll have the opportunity to shape the future of LMG and make a real difference in the lives of our customers.


This is a hybrid role (2 days in the office per week). We are looking for candidates in either Sydney (preferable) or Melbourne.


Duties and Responsibilities:

  • Design, develop, and implement AI and machine learning solutions to address complex business challenges.

  • Translate business problems into clear technical approaches, success measures and delivery plans.

  • Select appropriate approaches across generative AI, machine learning and statistical methods, balancing quality, complexity, cost and maintainability.

  • Establish evaluation frameworks, representative test datasets and automated checks to assess quality, reliability and business impact before and after release.

  • Work with Product, Engineering and Data Engineering to deliver scalable, maintainable AI solutions and integrate them into business products and workflows.

  • Guide the design of agentic workflows, including tool integration, access controls, failure handling and appropriate human review.

  • Establish and promote good practices for experimentation, testing, code review, documentation and responsible AI.

  • Communicate technical choices, trade-offs, limitations and recommendations clearly to stakeholders.

  • Mentor and guide junior data scientists to foster their growth and development.

  • Stay at the forefront of industry trends in AI, machine learning, and data science, driving innovation and continuous improvement within the team.

  • Communicate technical insights and recommendations effectively to both technical and non-technical stakeholders.


Skill and experience required:

  • A degree in Statistics, Computer Science, Data Science or a related quantitative field (Masters or PhD in Data Science will be an advantage)

  • 5+ years of hands-on experience in data science, including model development, deployment, and productionization.

  • Strong proficiency in Python and SQL for data manipulation, analysis, and machine learning model development.

  • Demonstrated experience delivering LLM applications, with practical knowledge of RAG, tool use and AI evaluation.

  • Strong foundations in statistics, machine learning and experimental design.

  • Experience deploying and operating solutions on cloud platforms and working with modern data infrastructure.

  • Proven ability to translate business problems into data science solutions and deliver impactful results.

  • Excellent communication and presentation skills with the ability to explain complex technical concepts to diverse audiences.

  • Experience mentoring others and improving technical practices within a team.

  • Experience delivering agentic AI workflows into production.

  • Experience with dbt or similar data transformation tools.

  • Experience applying AI in financial services or other environments involving sensitive data.

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