Senior Data Scientist

Ray White; Sydney; Hybrid; AUD 150,000 - 180,000; Full time

Job summary

LMG in Sydney/Melbourne is hiring a Senior Data Scientist to lead the development and deployment of cutting-edge AI and ML solutions. You will collaborate with business stakeholders, data engineers, software engineers and analysts to deliver impactful, data-driven outcomes.

The role is hybrid (2 days in office weekly). You will shape the future of AI within LMG, drive responsible practices, and mentor junior data scientists while staying ahead of industry trends in AI and data science.

Qualifications

• Degree in Statistics, Computer Science, Data Science or related quantitative field.
• 5+ years of hands-on data science experience including model development, deployment and productionization.
• Strong proficiency in Python and SQL for data manipulation, analysis and ML model development.
• Demonstrated experience delivering LLM applications with practical knowledge of RAG, tool use and AI evaluation.
• Strong foundations in statistics, ML 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 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.

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, ML 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.

Skills

Python

SQL

Statistics

ML deployment

LLM applications

RAG

Cloud platforms

Education

Degree in Statistics

Masters/PhD in Data Science (advantage)

Tools

dbt

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.