IS&T Specialist Data Science - Brisbane

Specialist Data Scientist - Brisbane

• Are you driven to solve complex tasks through creative and unique approaches?
• Join a growing product-focused organisation, creating solutions that matter for users that genuinely care about the outcomes.
• Diverse & challenging projects with our PACE Analytics team

About the role 

We're seeking data scientists to join the Analytics arm of Data & Analytics in Brisbane.

At a glance:

We are an analytics product team with a focus on end-user engagement and value delivery in our work.

We collaborate with Scientists, Engineers, and Industry Professionals across the business to accomplish this.

You have the opportunity to influence our engineering, quality, and knowledge practices as a part of this engagement.

Our team is focussed on a culture of inclusion, independence, and creativity, and supports flexible and WFH arrangements within the hub.

This role reports to the Principle Data Scientist and is part of our PACE Analytics team within IS&T.

Data-Science roles typically have diverse, multi-industry backgrounds and comprehensive skills in the fields of data modelling, engineering, and visualisation, as well as experience with advanced analytics techniques including machine learning and optimisation. These skills are used to turn data into information that can be used to make improved decisions and generate competitive advantage for Rio Tinto.

What you’ll bring 

Our team isn't one-size-fits-all and we've got a broad range of opportunities in our data-landscape.

*Attitude, motivation, and intuition carry as much weight as your technical background in our recruitment process*

We're hoping you're someone who has:

Experience in Data-Science product delivery, with a focus on Machine Learning and Artificial Intelligence solutions.

Data exploration, experimentation, analysis, and model development skills.

Experience with some (but not all!) of the common data-science libraries such as Numpy, Pandas, Keras, PyTorch, Scikit-Learn, Seaborn, and OpenCV.

An interest in helping a team grow our practices in Data Science processes, Product Quality Processes, Peer Review, and related dev culture.

Experience or Qualifications in Mathematics, Statistics, Computer Science or related fields.

*Some extra areas of experience to look at, but don't try and tick all of them off before you reach out:

Data: time-series, spatial, relational; streaming, batching, micro-batching; versioning, and serialisation.

Languages: Python (preferred), R.

A passion for articulation and storytelling from numbers and data. Probabilistic modelling and decision making in uncertain environments.

Awareness of software development practices and life cycles related to ML & AI.

Building-blocks like AWS Cloud, Postgres, Airflow, Sagemaker, Docker, mostly running on Linux.

DevTools such as DVC, Terraform, Azure DevOps, Docker, VSCode, PyCharm.

Test and Automation tools, CI/CD for ML, Pytest, MyPy, etc.

Or: if you've battled tested better stuff reach out and let us know.

Where you will be working

Data & Analytics is focused on improving performance through smarter ways of working by driving an innovative and “disruptive” technology culture. By partnering with Rio Tinto product groups and functions, our team is developing innovative ideas to solve problems and enable better decisions through data analytics.

Data is the backbone of Rio Tinto's assets: from mine to market, behind every product, are technological innovations that are driving new industry standards in mining and metals.

Every Voice Matters 

At Rio Tinto, we particularly welcome and encourage applications from Aboriginal and Torres Strait Islander people, women, the LGBTI+ community, mature workers, people with disabilities and people from different cultural backgrounds. 

We are committed to an inclusive environment where people feel comfortable to be themselves. We want our people to feel that all voices are heard, all cultures respected and that a variety of perspectives are not only welcome – they are essential to our success. We treat each other fairly and with dignity regardless of race, gender, nationality, ethnic origin, religion, age, sexual orientation or anything else that makes us different.