Datamine has offices in over twenty countries and more than 5000 customers, Datamine is a world leading provider of technology to plan and manage mineral exploration and mining operations. We provide solutions across the entire mining value chain including GIS, geological data management, laboratory systems, ore body modelling, mine planning, operations, logistics and commodity trading.

CCLAS EL, a product of Datamine, is an on premise LIMS solution that automates laboratory processes through versatile sample registration, barcode label printing, work list generation, online data capture from a wide range of analytical instruments, and automatic generation of analytical reports and commercial invoices. Datamine is currently migrating the functionality of CCLAS EL to a new web based LIMS we are calling CCLAS Mining.

ABOUT THE ROLE

The Product Owner translates laboratory needs into clear, testable specifications for CCLAS Mining and manages the product engineering activities within the AI Driven Development Life Cycle (AI-DLC). The role combines chemistry and laboratory knowledge with LIMS experience to ensure delivered functionality is scientifically correct, practical to use and aligned with customer needs.

Reporting to the Product Manager, this person will be working with the R&D; Manager, Business Analyst, developers and QA. The Product Owner defines expected behaviour, coordinates AI-assisted delivery and personally performs functional QA and usability testing. The role provides evidence and recommendations for product acceptance and release readiness.

KEY RESPONSIBILITIES

LABORATORY DISCOVERY AND PRODUCT SPECIFICATIONS

Liaise with customers (chemists’/laboratory managers) or consultants to understand workflows, operational problems, and priorities.



Map current and proposed processes and identify opportunities to reduce manual work and errors.

Translate needs into functional specifications, user stories, workflow diagrams, wireframes, and measurable acceptance criteria. Define business rules, data fields, validations, permissions, exception paths, and reporting requirements.

Specify workflows across sample receipt and registration, preparation, test allocation, instrument data capture, result calculation, QC review, authorisation, reporting, and invoicing, as relevant to each feature.

Define scientific rules precisely, including units, dilution factors, rounding, significant figures, detection limits, QC limits, retests, and amended results. Resolve ambiguities with laboratory subject matter experts.

Document integration and data requirements with technical specialists, including instrument interfaces, APIs, data mappings and migration or reconciliation rules. Define usability, performance, auditability, and data integrity expectations.

Maintain traceability between customer needs, approved specifications, changes, acceptance criteria, and test evidence. Manage specification versions and support backlog prioritisation with the R&D; Manager and Product Manager.

AI DLC DELIVERY AND PRODUCT QUALITY

MANAGE THE AI DLC PROCESS

Coordinate work from inception and specification through construction, validation,



and operational handover. Agree scope, dependencies, review points, and completion criteria with the delivery team.

Prepare and maintain the approved laboratory context, requirements, examples, and constraints supplied to AI tools. Break features into manageable work packages and keep specifications current as decisions change.

Review AI-generated plans, designs, specifications and test proposals for omissions, unsupported assumptions, and incorrect laboratory logic. Clarify requirements and direct rework before work proceeds.

Coordinate human review and approval at the required decision points. Record material decisions and ensure AI-generated deliverables are assessed against approved requirements and independently prepared expected results.

Track progress, defects, risks, and blockers. Escalate scientific, quality or delivery concerns and coordinate resolution with the Product Manager and R&D; Manager.

Use approved AI tools and protect customer information, intellectual property, and credentials. Use synthetic or appropriately de-identified laboratory data in prompts and test environments.

FUNCTIONAL QA AND USABILITY TESTING

Create and execute risk-based test plans for AI-DLC product output, covering functional behaviour, integrations, regression, and realistic laboratory scenarios. Collaborate with automation engineers on repeatable automated coverage.

Independently verify calculations, QC decisions, sample, and result traceability, reporting accuracy, permissions and audit trails using representative datasets and known expected outcomes.

Test normal workflows and failure conditions, including missing or invalid results, unit

📌 Product Owner (Brisbane)
🏢 Datamine Software
📍 Brisbane