Senior Data Scientist

Join to apply for the Senior Data Scientist role at Australian Energy Market Operator (AEMO)1 week ago Be among the first 25 applicantsJoin to apply for the Senior Data Scientist role at Australian Energy Market Operator (AEMO)AEMO at the Heart of EnergyAEMO is Australia's independent energy system and market operator and system planner.
AEMO's purpose is to ensure safe, reliable and affordable energy today, and enable the energy transition for the benefit of all Australians.
Australian governments are now committed to a net zero economy for Australia by 2050 and our vision is to enable this.
We have the once-in-a-lifetime opportunity to co-design the future of our energy systems, and our core values revolve around character, commitment, and connection.
Join us as we contribute to this significant transition in the energy sector.Division: OperationsDepartment: Modelling & EngineeringReference number: 12447Engagement type: PermanentAEMO at the Heart of EnergyAEMO is Australia's independent energy system and market operator and system planner.
AEMO's purpose is to ensure safe, reliable and affordable energy today, and enable the energy transition for the benefit of all Australians.
Australian governments are now committed to a net zero economy for Australia by 2050 and our vision is to enable this.
We have the once-in-a-lifetime opportunity to co-design the future of our energy systems, and our core values revolve around character, commitment, and connection.
Join us as we contribute to this significant transition in the energy sector.About The RoleOur team's bread and butter are the engineering apps and real-time analytics tools that help the control rooms make sense of the firehose of instreaming data, by combining and visualising many different data sources intelligently.
The AEMO control rooms monitor and operate the electricity grids and gas grids 24/7.
With AI trending relentlessly, and the integration of renewables providing a steady stream of challenges to solve, there has never been a more exciting time to be in the thick of it.The role entails working on projects and BAU initiatives, ranging from data preparation to full scale machine learning solutions.
You will design, build, train, compare, evaluate, deploy and document, using the state-of-the-art advancements of the past decade.
Some initiatives will involve other software developers and product team members.
Some initiatives might be solo and autonomous.
You will always work directly with the end users and SMEs.
Most of the time the end users will be electrical engineers and analysts in Operations, i.e. a highly technical audience.What You Will Be DoingWrite robust Python code for novel machine learning use cases and match the most appropriate machine learning approaches to engineering problems and take the lead in brain-storming sessions.Set the bar and guide junior team members to follow best practices for ML.Create and maintain meta data for Operations data sources in the data catalogue and data virtualisation environments.Take ownership of sharable artifacts such as graph database of the electricity grid assets and instigate knowledge sharing sessions with the Analytics User Group.Shadow the PSA Technical Lead as second-in-command for ITIL Service Management processes like IT Change Management.What Will You Bring To The RoleWe're looking for someone who has grappled with the idiosyncrasies of many ML projects and who proudly wears the scars.
Someone who stands their ground when inundated with hairy maths and dense academic papers, because their curiosity and excitement to solve problems always wins out.
Someone who likes to collaborate, mentor, and exchange knowledge, and who is totally comfortable admitting when they don't know.
An ability to sync up with the team's subtle but quirky sense of humour would be a bonus (fireship).
Plus the ability to shrug off the inevitable hurdles with a bit of tongue-in-cheek mockery, then quietly forging ahead.
relish the opportunity to take an initiative from inception all the way through to production deployment and support.Your experience includesSuccessful ML projects that are running in production.Many of the ML Python libraries such as Jax, Scikit-learn, PyTorch, TensorFlow, Wandb etc.Data cleansing, normalisation, one-hot encoding, and text embedding.Understanding graph data and time-series, and shaping them for ML modelsDeploying models, working with data pipelines, supporting production systems.Wrangling hardware drivers and config to offload matrix computations to GPU / TPU / NPU.At any stage a candidate may be asked to complete a data science challenge.If your resume mentions any showcase activities, for example on Kaggle, it will be taken into