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Gridsight

AI-powered utility grid capacity management

Senior/Staff Data Scientist - Optimisation

Data ScienceUpdated on Nov 15
Full-time

About the Job

Requirements

  • Strong understanding of existence and uniqueness of optima, ill-posedness, local versus global optimisation, gradient descent methods, least-squares minimisation, and non-convex optimisation.
  • Deep experience in constrained optimisation, operations research, or similar fields, including linear programming, convex optimisation, mixed-integer programming, and familiarity with optimisation solvers and frameworks such as Pyomo, CBC, Gurobi, CPLEX, and OR-Tools.
  • Knowledge of statistical modelling, numerical programming, algorithm design, and data analysis.
  • At least 5 years of experience in linear optimisation roles with demonstrated impact.
  • Ability to write quality code in Python for optimisation algorithms and data analysis; familiarity with architectural principles, system design, version control, testing practices, code review, and CI/CD.

Responsibilities

  • Solve constrained optimisation problems related to grid operations, resource dispatch, and network management.
  • Design optimisation solutions that balance safety, efficiency, customer impact, and operational constraints.
  • Collaborate with the grid modelling team to formulate network models and constraints as optimisation problems.
  • Build scalable optimisation solutions for 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.

Desired Qualifications

  • Grid domain knowledge, including electrical networks, power systems, and operational constraints.
  • Experience with network constraints, capacity expansion, or resource scheduling problems.
  • Experience with real-time or near-real-time optimisation systems.
  • Understanding of distributed energy resource integration challenges and battery or virtual power plant operations.
  • Experience with optimisation in high-performance contexts, such as metaheuristics or high-performance computing.
  • Experience in load forecasting.
  • Ability to work with customers to incorporate their existing forecasts into calculations.
  • Software engineering depth in system design, testing, deployment, and MLOps.
  • Familiarity with Databricks.
  • Experience instrumenting and analysing code performance with observability tools such as Datadog and Grafana.
  • Familiarity with data cleaning and data exploration.

About the Company

Gridsight

AI-powered utility grid capacity management

Gridsight is an AI-powered capacity-management platform for electric utilities that converts fragmented network data into a Foundational Grid Model tailored to each utility, so operators can identify where latent capacity exists and connect new load without building new infrastructure. It blends electrical physics with AI agents to support real-time hosting capacity, solar export management, and distribution planning. Unlike generic grid software, Gridsight delivers a utility-specific model that directly informs where and when to add capacity, enabling dynamic control over rooftop solar exports and faster planning. Its customers include Endeavour Energy, Xcel Energy, and United Illuminating. The company aims to expand its US footprint while continuing growth in Australia and other markets, supported by fundraising to accelerate expansion.

Company size
51-200
Company stage
Series B
Total funding
$28.2M
Headquarters
Wollongong City Council, Australia
Founded
2020

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