
Technical Lead Data Sciences
3 days ago
Fortescue is both a proud West Australian company and a global green solutions business. We are recognised for our culture, innovation and industry-leading development of infrastructure, mining assets and green energy initiatives.
Our OpportunityWork Location: Perth Office – Fortescue's Perth office is located on the traditional lands of the Whadjuk Noongar people
Roster: Monday to Friday
Fortescue's Data Science team delivers value and drives innovation through the disciplined application of the scientific method and agile delivery. We collaborate across the business to tackle real-world challenges and build solutions that move the needle. We're passionate about turning advanced analytics and AI into clear, actionable outcomes that support Fortescue's strategic goals.
From targeted opportunity identification and crisp problem definition through to production ML systems and measurable value realisation, our team enables transformation at scale. We go beyond technical delivery to create material, sustainable impact.
Effective leaders in Data & AI pair a future-back vision with a sharp focus on value, curiosity and creativity. They harness data, data science and AI to unlock new opportunities, solve complex challenges, streamline processes and enable strategic advancements aligned to Fortescue's vision.
Key Responsibilities- Translate enterprise strategy into a prioritised data science roadmap, shaping problem statements, defining value measures, and managing trade-offs with senior stakeholders
- Deliver decision-ready insights and data-driven recommendations, leveraging experimentation, A/B testing, and causal analysis to measure impact and drive business outcomes
- Lead structured requirements definition and change planning, ensuring data science solutions accelerate adoption and value realisation across the organisation
- Establish engineering standards and reusable frameworks for model reproducibility, feature stores, version control, CI/CD for ML, and observability across data science workflows
- Architect and design scalable, secure, and resilient data science solutions, ensuring seamless integration with enterprise data platforms and systems
- Oversee the end-to-end lifecycle of production-grade ML products, from discovery through delivery, deployment, monitoring, and continuous optimisation
- Ensure operational readiness and MLOps excellence, monitoring model drift, bias, and data quality while maintaining strong incident management and feedback loops
- Collaborate with Data Engineering teams to optimise data pipelines, storage, and compute performance, balancing accessibility, integrity, and cost efficiency
- Embed responsible AI principles — safety, fairness, privacy, explainability — and partner with governance, risk, and legal functions to maintain compliance and audit readiness
- Foster innovation and capability growth, piloting emerging technologies (GenAI, LLMOps, computer vision, causal inference) and mentoring teams through knowledge sharing and playbook development.
- Bachelor's degree in Data Science, Computer Science, Software Engineering, mathematics, statistics, machine learning, or a related field. Postgraduate study preferred
- Experience (5+ years) in applied data science/ML with demonstrable impact; resources, energy, green energy, or heavy industrial operations preferred
- Experience (3+ years) leading cross-functional data science/data engineering product teams, including technical direction and senior stakeholder engagement
- Track record delivering production ML systems (batch and streaming) with measurable business outcomes and mature MLOps practices
- Depth in statistics and machine learning (classical ML, NLP including LLMs, computer vision, predictive analytics) and experimental design
- Proficiency in Python and SQL; practical experience with ML frameworks (e.g., TensorFlow, PyTorch) and experiment tracking tools
- Strong software engineering foundations and practical experience with Git-based workflows and CI/CD
- Proficiency with modern data/ML platforms and cloud services (e.g., Databricks or SageMaker; Snowflake; S3/object storage; event streaming such as Kafka; AWS or Azure)
- Demonstrated ability to set technical standards, conduct rigorous reviews (code/model/data), and uplift team capability
- Strong stakeholder relationship management and presentation skills; able to translate complex concepts for executives and frontline users alike
- Ability to monitor and leverage emerging technologies to drive innovation while balancing risk, value, and feasibility.
Fortescue is deeply committed to providing a safe culture that builds respect, fosters inclusiveness, and values diversity. We celebrate individual strengths and team members from all backgrounds are encouraged to bring their whole selves to work. Our global workforce drives and promotes an inclusive culture, both within our organisation and throughout the communities we interact with across the world. Diverse backgrounds include First Nations Peoples, people with differing abilities, LGBTIQ+ community, gender, neurodiverse, cultural diversity, all age groups, and those with an intersectional or multiple diverse characteristics. We encourage candidates from all backgrounds to apply.
Internal Candidates / Current Contractors please apply via Success Factors Careers Portal. For further information on how to apply please visit the Fortescue Hub.
Fortescue reserves the right to close applications early should a suitable pool of candidates be identified. Fortescue will never contact you to ask for payment of any kind, whether directly or through a third party.
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