Data Scientist (Energy)

Trades Workforce Solutions; Council of the City of Sydney; On-site; AUD 90,000 - 120,000; Full time

Job summary

A cutting-edge Energy Technology business in Sydney is seeking a Data Scientist (Energy) to join their team. This role involves sourcing and analyzing large datasets, developing energy models, and collaborating with product teams. Applicants should have a quantitative background with strong skills in energy modeling, data analysis, and Python programming. The position offers an opportunity to contribute to the energy transition sector in a rapidly growing company.

Qualifications

• Previous experience in energy modelling focused on Australian power systems.
• Strong quantitative skills and ability to solve complex technical problems.
• Excellent technical communication skills for explaining concepts to non-technical stakeholders.

Responsibilities

• Source, process, analyze, and interpret large datasets.
• Develop power market and dispatch models using Python and scientific computing stack.
• Collaborate with product and analytics teams to align products with user needs.

Skills

Energy modelling

Data analysis

Machine learning

Optimization techniques

Technical communication

Education

Degree in a quantitative field

Tools

Python

Numpy

Pandas

SciPy

ScikitLearn

Job description

Data Scientist (Energy)
Sydney, Australia

Enemix has partnered with an exciting cutting edge Energy Technology business that has had great success and 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 experience Data Scientists 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 [e-mail]