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 & ML Ops 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 5 years of python development experience
• You have at least 3 years of commercial experience working with data scientist/ML researchers to develop tooling, collaborate on backtesting frameworks, build data pipelines, build/maintain orchestration workflows or productionise code.
• Proficiency with Orchestration and IaC (Airflow, ECS, Kubernetes, Terraform, CloudFormation), Git, Containerization (docker), SQL (Postgres, Snowflake)
• 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.

Extra credit if you can demonstrate:

• Data engineering experience collecting, curating, managing and monitoring large timeseries data
• Experience with monitoring frameworks (e.g. Prometheus)
• Machine learning experience especially time-series forecasting & generative ML problems
• Experience with optimization methods especially linear programming / mixed-integer programming.
• Knowledge of a US ISO power market (especially ERCOT)
• Experience with data visualization and dashboarding technologies (e.g. plot.ly, Dash, Streamlit)

• 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 day in our offices in Austin.

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