Senior/Staff Data Scientist (Optimisation)

The Role

As a Senior/Staff Data Scientist (Optimisation), you will design, implement and run the optimisation engines that power modern 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