Data-Scientist-Energy role in Sydney

In short

Enemix has partnered with a cutting-edge energy technology company to hire a Data Scientist with energy or power systems expertise who will develop models and revenue projections for the energy transition in Sydney.

Highlights

  • Develop and enhance power market and dispatch models using Python and scientific computing tools to create reliable revenue projections and analytics across complex energy systems.
  • Source, process and analyse large, complex datasets while collaborating closely with product and analytics teams to ensure insights align with user needs and support the energy transition.
  • Bring a strong background in energy modelling with 5+ years of Python (or similar language) experience, a quantitative degree, and the ability to communicate complex data science concepts to non-technical stakeholders.
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More about this Data-Scientist-Energy  Role

Enemix has partnered with an exciting cutting edge Energy Technology business that has had great success in the UK and Europe. They’ve recently joined the Australian market and are quickly becoming a leading name in the Energy transition sector. Their mission is to create the definitive information framework for the energy transition, fostering a great team to do it together.

Given the technologies and services they offer, they are looking for an experienced Data Scientist with an Energy or Power Systems background to join the Sydney team. It is crucial that you have a desire to grow and learn, be a part of a rapidly growing company, and have an appetite to work in an exciting start-up environment.

The Role

As a Data Scientist you will be part of an established team that leverages their expertise to develop innovative, industry-leading models and analyses. They create tools used by organizations across the energy transition to finance, build, benchmark, and operate complex Energy systems. This position is within our data science team, focusing on creating reliable revenue projections across various regions.

Responsibilities:

* Source, process, analyse, and interpret large and complex datasets within our expanding forecast offering.
* Develop our power market and dispatch models to enhance their product offerings. We utilise Python and the standard scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.).
* Collaborate closely with our product and analytics teams to ensure the products they deliver align with user needs and add value to the broader team.
* Focus on creating reliable revenue projections across various regions.
* Finance, build, benchmark, and operate complex projects across the innovative Energy Systems.

Qualifications:

* Previous experience in energy modelling, particularly focusing on the Australian power systems.
* A degree in a quantitative field such as mathematics, engineering, computer science, physics, or a related discipline.
* Strong quantitative skills with a proven track record of solving complex technical problems using data analysis, machine learning, and optimization techniques.
* Demonstrated ability to produce data science models and insights delivered directly to external customers, with experience handling high-visibility, customer-facing outputs.
* Excellent technical communication skills, capable of explaining complex data science concepts to non-technical stakeholders.
* Over 5 years of experience using Python (or another programming language such as R, C++, Java) and the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.).

If you're interested in hearing about the role please apply or send your CV to karina.wright@enemixgroup.com

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Job Title

If you feel you would be suitable for this Data-Scientist-Energy   role then please apply below and your specialist consultant Karina Wright  will be in touch with you, alternatively, you can reach out the them directly by calling  02 9129 2265

Location

This job is located in SydneyNSW

Employment Type

Full-time

Salary information

The available salary for this role is Negotiable depending on experience

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