Senior Data Scientist

Ray White; Melbourne; Hybrid; AUD 140,000 - 190,000; Full time

Job summary

LMG is seeking a Senior Data Scientist to lead AI and ML initiatives, translating business goals into scalable data solutions. You will work with data engineers, product and software teams to deliver impact while mentoring juniors and promoting responsible AI practices.

The role is hybrid with 2 office days per week, located in Sydney or Melbourne, focusing on cutting‑edge AI applications and productionizing models for business use.

Qualifications

• Degree in Statistics, Computer Science, Data Science or related quantitative field (Masters/PhD advantageous).
• 5+ years hands-on data science experience including model development and productionization.
• Proficient in Python and SQL for data manipulation and ML model development.

Responsibilities

• Design, develop and implement AI/ML solutions to address business challenges.
• Translate problems into technical approaches, success measures and delivery plans.
• Establish evaluation frameworks and automated checks for quality and impact before/after release.
• Collaborate with Product, Engineering and Data teams to deliver scalable AI solutions.
• Mentor junior data scientists and promote best practices in experimentation and code reviews.
• Communicate insights clearly to technical and non-technical stakeholders.
• Stay current with AI/ML trends and drive continuous improvement.

Skills

Python

SQL

LLM applications

RAG

Statistics

Cloud platforms

Data infrastructure

Communication

Mentoring

Agentic AI workflows

dbt

Data transformation

Financial data

Education

Statistics / CS / Data Science degree

Tools

dbt

Job description

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.

  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.