Lead Data Scientist

Adactin Group; Melbourne; On-site; AUD 150,000 - 190,000; Full time

Job summary

Adactin Group in Melbourne seeks a Lead Data Scientist to design, develop and deploy advanced AI/ML solutions across structured and unstructured data. You will deliver actionable insights to optimise operations and support strategic decisions, using generative AI, LLMs and RAG pipelines.

The role requires expertise in statistical modelling, lifecycle management of models, and responsible AI practices, with leadership to guide projects and teams within a dynamic IT consulting environment.

Qualifications

• Strong experience in data science, artificial intelligence, machine learning and statistical modelling.
• Hands-on expertise in designing, developing and optimising AI/ML solutions.
• Experience with generative AI, LLMs, Retrieval-Augmented Generation (RAG), prompt engineering and agentic AI workflows.
• Strong knowledge of data preparation, cleaning, transformation, feature engineering and data modelling.
• Experience in AI model training, validation, evaluation, deployment and performance optimisation.
• Knowledge of Responsible AI principles, model governance, safety assessments and explainability.

Responsibilities

• Lead the design and implementation of AI and machine learning solutions aligned with business and operational objectives.
• Manage data acquisition, integration, transformation and feature engineering across complex datasets.
• Design and deliver proof-of-concept initiatives, model experimentation, validation and performance evaluation.
• Develop and optimise generative AI solutions, including LLMs, RAG pipelines, prompt engineering and agentic AI workflows.
• Establish evaluation frameworks to assess model accuracy, performance, safety and business outcomes.
• Lead model deployment, integration, monitoring and continuous improvement across the model lifecycle.
• Apply statistical and machine learning techniques to identify trends, generate insights and solve complex business problems.
• Implement Responsible AI practices, including bias assessment, fairness, explainability, model assurance and governance.
• Engage with stakeholders to understand business requirements and translate analytical findings into actionable recommendations.
• Lead technical reviews, maintain solution documentation and ensure quality standards.
• Provide technical leadership, guide team members, set priorities and manage resources to achieve business outcomes.

Skills

Data science

AI/ML

Generative AI

LLMs

RAG

Prompt engineering

Agentic AI

Model lifecycle

Statistical modelling

Stakeholder comms

Job description

Adactin Group is a 100% Australian-owned global IT consulting company, headquartered in Sydney. We are a trusted technology partner helping organizations drive end-to-end digital transformation through our deep expertise in Microsoft and AWS ecosystems, AI-powered Digital Engineering, and future-ready Quality Assurance.

Our managed delivery approach, backed by domain expertise, ensures successful outcomes for every project. At Adactin, we believe in the power of our people. We foster a dynamic and supportive environment where your career can grow alongside exciting projects that shape the future of technology. Join us, and be part of a team committed to innovation, excellence, and making a difference.

About the Role

We are seeking an experienced Lead Data Scientist to lead the design, development and implementation of advanced data science, artificial intelligence and machine learning solutions. The role involves working with structured and unstructured data to deliver actionable insights, optimise operational processes and support strategic decision-making.

The successful candidate will bring strong expertise in statistical modelling, generative AI, large language models (LLMs), Retrieval-Augmented Generation (RAG) and end-to-end model lifecycle management.

Key Responsibilities

• Lead the design and implementation of AI and machine learning solutions aligned with business and operational objectives.
• Manage data acquisition, integration, transformation and feature engineering across complex datasets.
• Design and deliver proof-of-concept initiatives, model experimentation, validation and performance evaluation.
• Develop and optimise generative AI solutions, including LLMs, RAG pipelines, prompt engineering and agentic AI workflows.
• Establish evaluation frameworks to assess model accuracy, performance, safety and business outcomes.
• Lead model deployment, integration, monitoring and continuous improvement across the model lifecycle.
• Apply statistical and machine learning techniques to identify trends, generate insights and solve complex business problems.
• Implement Responsible AI practices, including bias assessment, fairness, explainability, model assurance and governance.
• Engage with stakeholders to understand business requirements and translate analytical findings into actionable recommendations.
• Lead technical reviews, maintain solution documentation and ensure quality standards.
• Provide technical leadership, guide team members, set priorities and manage resources to achieve business outcomes.

Essential Skills and Experience

• Strong experience in data science, artificial intelligence, machine learning and statistical modelling.
• Hands-on expertise in designing, developing and optimising AI/ML solutions.
• Experience with generative AI, LLMs, Retrieval-Augmented Generation (RAG), prompt engineering and agentic AI workflows.
• Strong knowledge of data preparation, cleaning, transformation, feature engineering and data modelling.
• Experience in AI model training, validation, evaluation, deployment and performance optimisation.
• Knowledge of Responsible AI principles, model governance, safety assessments and explainability.
• Ability to communicate complex technical concepts and insights to business stakeholders.
• Proven experience leading analytical projects, reviewing deliverables and guiding technical teams.

Technical Expertise

• Artificial Intelligence and Machine Learning
• Statistical Modelling and Advanced Analytics
• Generative AI and Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering and Agentic AI
• Data Modelling, Data Cleaning and Feature Engineering
• Model Evaluation, Monitoring and Optimisation
• Responsible AI, Model Assurance and Governance

Due to the nature of the role, candidates must be Australian citizens. A Baseline security clearance is desirable.