Senior/Staff Data Scientist (Optimisation)

The Role We're hiring a Senior or Staff-level Data Scientist to help design and build the powerflow and optimisation engines at the core of our platform. This role sits at the heart of our work on calculating safe, real-time capacity for distributed energy resources within network constraints and turning those calculations into forecasts and dispatch, resource allocation, and grid management decisions that affect how networks actually operate. This is applied optimisation work. You'll formulate constrained optimisation problems, implement algorithms, and build systems that run in real-time or near-real-time operational contexts. You'll work closely with the rest of the Grid Modelling team to translate network physics into optimisation constraints and get solutions into production. What you'll do Develop powerflow engines for grid modelling and forecasting 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 What you'll bring Powerflow and/or optimisation expertise: Deep experience with one or both of AC optimal powerflow (AC-OPF) calculations, including the use of key open-source packages such as OpenDSS, pandapower and lf-energy, 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 data science/ML/optimisation roles with demonstrated impact Python proficiency: Capable of writing quality code for optimisation algorithms and data analysis; familiar with architectural principles, system design, version control, testing practices, code review, CI/CD What would set you apart Grid domain knowledge (electrical networks, power systems, operational constraints) Experience with market dispatch, energy economics, or resource scheduling problems Real-time or near-real-time optimisation system experience Understanding of DER integration challenges and VPP operations Experience in highly parametric statistical model fitting, e.g. state estimation for energy networks 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 Familiarity with data cleaning and data exploration What we offer $160k–$220k depending on experience, plus equity Remote-first, with head office in Sydney A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter Sound interesting? We'd love to hear from you! Apply directly and we'll be in touch shortly.