The Role

As a Senior/Staff Data Scientist (Optimisation), you will design, implement and run the optimisation engines that power contemporary dynamic electricity grids. Your solutions will allow electricity utilities to efficiently manage grid constraints and resources, to forecast grid state into the future, and to assess connection applications for new renewables projects in record time. Key Accountabilities

Solve constrained optimisation problems related to grid operations, resource dispatch, and network management

Design optimisation solutions that balance multiple objectives (safety, efficiency, customer impact, operational constraints)

Collaborate with others in the grid modeling team to formulate network models and constraints as optimisation problems

Build scalable optimisation solutions that perform in real-time or near-real-time operational contexts

Establish best practices for optimisation model development, validation, and monitoring

Contribute to technical strategy for data science, optimisation capabilities and future applications

Core Requirements

Optimisation fundamentals: Strong understanding of existence and uniqueness of optima, ill-posedness, local vs global optimisation, gradient descent methods, least squares minimisation, non-convex optimisation Linear optimisation expertise: Deep experience in constrained optimisation, operations research, or similar fields (linear programming, convex optimisation, mixed-integer programming, familiarity with optimisation solvers and frameworks such as Pyomo, CBC, Gurobi, CPLEX, OR-Tools, etc.)

Data science foundations: Statistical modeling, numerical programming, algorithm design, data analysis

Senior/Staff level experience:



5+ years in linear optimisation roles with demonstrated impact

Software engineering prowess: Capable of writing quality code in Python for optimisation algorithms and data analysis; familiar with architectural principles, system design, version control, testing practices, code review, CI/CD

Differentiators

Grid domain knowledge (electrical networks, power systems, operational constraints)

Experience with network constraints, capacity expansion or resource scheduling problems

Real-time or near-real-time optimisation system experience

Understanding of DER integration challenges and battery/VPP operations

Experience with optimisation in high-performance contexts, e.g. use of metaheuristics, HPC

Experience in load forecasting

Ability to work with customers to incorporate their existing forecasts into your own calculations

Software engineering depth (system design, testing, deployment, MLOps)

Familiarity with Databricks

Experience instrumenting and analysing code performance with observability tools (e.g. Datadog, Grafana)

Familiarity with data cleaning and data exploration

What We Offer

Competitive salary. We hold high expectations, but pay accordingly.

Meaningful ESOP so you share in the growth of Gridsight.

$2,500 WFH allowance, $2,500 health and wellness allowance, bi-annual in person working weeks, and lunch is on us when you’re in office.

Work how you like. Fully remote, hybrid or in office with a fresh, new head office in Sydney and satellite spaces in Melbourne, Brisbane and Hobart.

Learn More

Brendan Banfield (CEO at Gridsight) in conversation with James Cameron (Partner at Airtree)

Gridsight's work with Endeavour Energy to deliver flexible exports The problem space we're tackling

📌 Senior/Staff Data Scientist (Optimisation) (City of Wollongong)
🏢 GRIDSIGHT
📍 City of Wollongong