Design and deploy data science and numerical modelling solutions for electricity grid components; build data pipelines, validate and productionise ML models; collaborate with engineering and product teams and engage with customers to meet requirements and maintain MLOps and software engineering best practices.
Electricity grids are undergoing the most significant transformation in a century. The shift to renewables, the proliferation of rooftop solar, batteries, and EVs, and the increasing complexity of distribution networks are forcing utilities to operate their grids in fundamentally new ways.
Gridsight builds the analytics platform that makes this possible. We're already embedded with most of Australia's major distribution networks and have contracts with some of the largest investor-owned utilities in the United States. We're well-funded, growing quickly, and positioned at the centre of a global shift toward dynamic grid management.
The roleWe're hiring a Senior or Staff-level Data Scientist to design and develop software and data science tools for modelling usage and generation of electricity. Your work will enable electrical utilities to manage the growth and operation of their distribution networks through advanced data analytics, allowing them to get more renewables into the grid, sooner.
What You'll Do- Design, build, and maintain software products and data science models capable of simulating or predicting key components, properties and events of electricity grids, including individual connections to the grid such as power assets, commercial, industrial, agricultural and infrastructure projects
- Obtain data from disparate sources to inform and support modelling, by performing data discovery and/or developing automated retrieval pipelines as needed
- Ensure software and model capabilities, coverage and performance align with customer requirements, directly engaging with customers from time to time in order to do so
- Collaborate with Software Engineers, Data Engineers, and other Product teams to understand data science requirements and translate them into technical solutions
- Establish and follow data, scientific, MLOps and software engineering best practices including testing, validation, documentation, monitoring, version control and code reviews
- Contribute to data science strategy and architectural decisions
- Senior/staff level experience: 5+ years in data science roles with demonstrable impact
- Software engineering fundamentals: proficiency in Python or similar language, architecture, system design, version control, testing practices, code review, CI/CD
- Numerical modelling: mathematical modelling, numerical methods, applied statistics
- ML modelling: experience developing, training, testing and validating machine learning models, as well as deploying them to production
- Customer-facing experience: experience delivering software/data products to customers, and iterating based on their feedback.
- Experience building data products for customer consumption
- Experience in energy, utilities, or IoT/sensor data domains
- Experience with time-series data or operational analytics
- Experience with business process modelling
- Experience discovering and integrating diverse data sources into complex modelling pipelines, both ML and otherwise
- Experience designing and implementing agentic workflows
- Experience optimising Python workflows, e.g. via parallel/distributed solutions or development of interfaces to optimised lower-level libraries
- Experience working in remote or distributed teams
- Data governance or compliance experience in regulated industries
- Competitive salary and equity package
- Remote-first, with head office in Sydney
- A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter
Top Skills
CircleCI
Git
Github Actions
Gitlab Ci/Cd
Jenkins
Keras
Mlops
Python
PyTorch
Scikit-Learn
TensorFlow
Gridsight Sydney, New South Wales, AUS Office
Sydney, New South Wales, Australia
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