Principal Data Scientist

Principal Data Scientist The Digital WAIO team builds and operates reliable, safe and impactful solutions that improve operational decision-making across complex systems. This includes applying decision science, optimisation and advanced analytics techniques across planning, scheduling and operational use cases. As Principal Data Scientist, you will work closely with technical and operational stakeholders to design and deliver robust, production‑ready decision‑support solutions. You will contribute to a growing decision science capability, supporting the translation of complex problems into practical, scalable outcomes that improve safety, productivity and cost performance. Responsibilities Be connected to operational stakeholders and collaborate to frame complex problems into structured analytical solutions Design and develop analytical models and decision‑support solutions across planning, scheduling and operational systems, using a combination of optimisation, machine learning and statistical techniques Apply a range of techniques including optimisation (e.g. linear and mixed‑integer programming, heuristics), simulation‑supported approaches, machine learning and statistical models; selecting the right method for the problem and the operational context Build, deploy and support production‑ready analytical models and pipelines, ensuring solutions are scalable, reliable and maintainable Collaborate with engineering and data teams to integrate models into systems, workflows and digital products Monitor and maintain deployed models, including performance, stability, data quality and ongoing improvement Contribute to broader analytics initiatives including simulation, machine learning and emerging digital capabilities, helping shape standards, tools and best practices Build trusted relationships across technical and non‑technical stakeholders to enable successful delivery of outcomes Qualifications Experience applying data science, optimisation or other advanced analytical techniques to real‑world problems Strong programming capability in Python, with experience writing maintainable and production‑quality code Demonstrated experience delivering analytical solutions into operational or production environments Experience developing, validating and deploying machine learning or statistical models in applied or industrial contexts Experience working with stakeholders to define problems, assumptions and value outcomes Demonstrated ability to collaborate with external vendors, partners or co‑build teams to design, deliver and support analytical solutions Demonstrated ability to collaborate across technical teams, including engineering, data and domain specialists Understanding of model lifecycle management, including deployment, monitoring and ongoing support Experience working within or alongside complex operational environments Experience with cloud platforms (AWS or Azure), cloud‑based data services and an understanding of security, cost and reliability considerations in cloud environments Tertiary qualification in a relevant quantitative or technical discipline such as Mathematics, Statistics, Engineering, Computer Science Experience in mining, resources, supply chain or industrial operations Exposure to scheduling or planning systems and large‑scale optimisation problems Experience with simulation or system modelling approaches Familiarity with MLOps or analytics deployment practices Benefits We offer flexible working options, generous paid parental leave, extended leave entitlements and parent rooms. Equal Opportunity Employer BHP is an Equal Opportunity Employer committed to a safe and inclusive workplace where everyone can thrive and be at their best. We are focused on creating a workforce that’s diverse and represents the communities where we work and live. For applicants with a disability, we may adjust our recruitment process to ensure fairness. If you would like to discuss your situation, please email us at View email address on click.appcast.io. #J-18808-Ljbffr BHP Group