Data Science Intern

5 hours ago


Elizabeth St Melbourne VIC Australia Melbourne Australia Blunomy Full time $60,000 - $80,000 per year

Blunomy is an international consulting firm, dedicated to accelerating the move towards a regenerative society that is decarbonised, circular and inclusive. We do this by partnering with those in the energy supply chain as well as financial institutions, businesses and entrepreneurs to ensure the transition of their resources from brown to green.

We have been operating since 2007, previously trading as Enea Consulting, and continue to expand our international team of Blunomists. Our high performing, multidisciplinary team are based across 6 offices: Melbourne, Sydney, Paris, Singapore, Hong Kong and London. We come from a wide variety of backgrounds and experiences, are open minded and focused on the future, united by shared values and are passionate about sustainable development and energy access.

We are looking for a passionate, engaging, and ambitious Inter to join our team in either Melbourne or Sydney. We invite all of those who want to break the mould to join us to get change done

About the role: Data analytics in the energy and climate space is growing at an incredible rate. Blunomy provides data-based solutions to support the energy industry, financial institutions and supply chains through their digitisation, decentralisation and decarbonisation transitions. Our tools support improved energy market operability, automation and planning. We are also developing digital solutions that better measure impact and transition speed, to help channel financial resources from brown to green.

We are looking for someone who is passionate about energy, climate change and data analytics to do-well-and-do-good by delivering data science products to crack transition challenges. As an Analyst Intern (6 month duration) you will work on projects under the supervision of project managers.

In this setting, you will be exposed to the diversity of current energy challenges, leveraging your data and analytical skills to address them. We are always growing the products we deliver but over the last 12 months we have delivered:

  • Load forecasting: model and predict the evolution of the load on the electrical network. Use machine learning, data analytics and a fair amount of software development to forecast long-term energy consumption, daily energy profiles and Distributed Energy Resources (Electric Vehicles, Battery, Solar PV).

  • PV connections approval tool: dynamically model the energy network bringing together power flow modelling and machine learning to determine the PV hosting capacity of the local area. Used in production to approve hundreds of PV connection requests a day.

  • Vegetation management using LiDAR: collect three dimensional images of the local network gathered by drone or helicopter. Use machine learning and geometric models to detect and manage vegetation near powerlines.

  • Bushfire risk modelling: model and compute the network‑related bushfire risk based on fault ignition likelihood. Calculate the consequences of bushfires such as property damage or agricultural loss.

  • Low-Voltage network mapping: identify errors within the current mapping of the low-voltage network, especially targeting customers whom connection to the network has not been properly recorded. This was performed using outlier detection with out-of-bag predictors.

Depending on the objectives, projects will entail tasks of varying nature. Your first focus will be on projects requiring data analytics capabilities.



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