Senior Data Scientist

1 week ago

Melbourne, Victoria, Australia Australian Energy Market Operator (Aemo) Full time

Join to apply for the
Senior Data Scientist
role at
Australian Energy Market Operator (AEMO)
.
AEMO at the Heart of Energy. AEMO 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: Operations
Department: Modelling & Engineering
Reference number: 12447
Engagement type: Permanent
Our 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 Doing
Write robust Python code for novel machine learning use cases and match the most appropriate ML approaches to engineering problems, and lead brainstorming sessions.
Set the bar and guide junior team members to follow best practices for ML.
Create and maintain metadata for Operations data sources in the data catalogue and data virtualization environments.
Take ownership of sharable artifacts such as the graph database of the electricity grid assets and initiate knowledge sharing sessions with the Analytics User Group.
Shadow the PSA Technical Lead as second-in-command for ITIL Service Management processes such as IT Change Management.
Your experience includes
We're looking for someone who has grappled with the idiosyncrasies of many ML projects and who is curious and excited to solve problems. They should enjoy collaborating, mentoring, and exchanging knowledge, and be totally comfortable admitting when they don't know. A sense of humour would be a bonus. A willingness to take initiative from inception through production deployment and support is valued.
Successful ML projects that are in production.
Experience with ML Python libraries such as Jax, Scikit-learn, PyTorch, TensorFlow, Wandb, etc.
Data cleansing, normalization, one-hot encoding, and text embedding.
Understanding graph data and time-series, and shaping them for ML models.
Deploying models, working with data pipelines, and supporting production systems.
Wrangling hardware drivers and configs 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

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