Senior Data Scientist

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.

Desirable experience

• 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.

• Desirable experience

• 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.