Data Scientist

Habitat Energy – Data Scientist US (Experienced)

At Habitat Energy we bring together exceptionally talented and passionate people in the domains of data science, software engineering and energy trading alongside an in-depth understanding of flexible energy assets. Our aim is to maximise the value of grid-scale battery storage, so they are attractive investments, are deployed at scale and enable the energy transition.

We are looking for smart, motivated people to join our team who share our belief that we can outperform the energy sector dinosaurs, have a positive impact on the planet and have fun doing it together.

We have a vacancy for an experienced Data Scientist to join our team. You will be working on the development of our renewables trading platform in the US:

• Lead the development and productionization of our renewables trading (DA optimisation of virtual and asset backed DART etc.)
• Closely collaborate with the commercial and business development team on aligning models with market and client needs
• Bringing an experimental mindset, prototyping and developing with the right model for the job.

We’re looking for someone who is a great fit for our company. We want people who take accountability, build trust and are innovative. We encourage you to apply even if you may not meet every requirement in this posting. We value diversity and our environment is supportive, challenging and focused on the consistent delivery of high quality, meaningful work.

Requirements:

• You have at least 3 years of commercial experience developing and productionising real-time projects in Machine Learning and Data Science.
• Experience with short term US power markets
• Experience building algorithmic decision tools (e.g. mixed-integer linear programming, CVXPY).
• You have experience bringing your creative output to support development of quarterly product roadmaps.
• You are fluent in Python and its wider numerical ecosystem (Pandas, NumPy, Scikit-learn, Polars, etc.).
• You have a BA/BSc degree in Computer Science, Machine Learning, Electrical Engineering, or related technical field.
• Version control code (Git) including dev, test and production environments.

Extra credit if you can demonstrate:

• Experience trading virtual and/or asset-backed positions in one or more major US Power Market (ideally ERCOT)
• Electricity & energy domain modelling (e.g. power systems modeling, power flow, security constrained unit commitment etc.)
• Full-stack / machine learning engineering / data engineering experience
• Experience with forecasting & time series problems
• Experience with data visualization and dashboarding technologies (e.g. plot.ly, Dash, Streamlit)
• Demonstrated track record of academic paper (NeurIPS, ICLR, ICML; and/or papers on power systems, optimization or other related topics)
• AWS, terraform, continuous integration, monitoring and alerting.
• MS or PhD degree in Computer Science, Machine Learning, or related technical field.

In return, we’ll give you a competitive salary, flexible working arrangements and a lot of personal development opportunities. We operate a hybrid working model with at least 2 days in our offices in Austin.

When you apply for a job with us, we process some of your personal information. You can find out more about how we process your information in our candidate privacy policy, here.