Data Scientist / Senior Data Scientist (Grid Insights)
Purpose
You will design and develop software and data science products that provide electricity utilities key insights into the state and operation of their grids. Beginning with detection and disaggregation of DER resources, your work will help to build up the picture of how grids can be managed more efficiently and dynamically, paving the way for the connection of more renewables, sooner.
Key Accountabilities
Design, build, and maintain software products and data science models capable of detecting, characterising or predicting key components, properties and events of electricity grids.
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
Core Requirements
Experience: 3+ years in data science roles with demonstrable impact. PhD not required, but completion of a doctorate with a relevant focus on data science – especially Bayesian methods – may be counted towards this requirement.
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
Differentiators
Experience with Bayesian methods (parameter estimation, hierarchical modelling, sampling, etc)
Experience with Monte Carlo methods
Experience in energy, utilities, or IoT/sensor data domains
Experience building data products for customer consumption
Experience delivering software/data products to customers, and iterating based on their feedback.
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
What We Offer
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
A role with clear growth pathways into product and tooling, or deeper customer ownership
You will design and develop software and data science products that provide electricity utilities key insights into the state and operation of their grids. Beginning with detection and disaggregation of DER resources, your work will help to build up the picture of how grids can be managed more efficiently and dynamically, paving the way for the connection of more renewables, sooner.
Key Accountabilities
Design, build, and maintain software products and data science models capable of detecting, characterising or predicting key components, properties and events of electricity grids.
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
Core Requirements
Experience: 3+ years in data science roles with demonstrable impact. PhD not required, but completion of a doctorate with a relevant focus on data science – especially Bayesian methods – may be counted towards this requirement.
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
Differentiators
Experience with Bayesian methods (parameter estimation, hierarchical modelling, sampling, etc)
Experience with Monte Carlo methods
Experience in energy, utilities, or IoT/sensor data domains
Experience building data products for customer consumption
Experience delivering software/data products to customers, and iterating based on their feedback.
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
What We Offer
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
A role with clear growth pathways into product and tooling, or deeper customer ownership