Data Scientist

Data Scientist
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 forecasting and algorithmic trading platform in the GB power market:
Building machine learning models to forecast demand, market prices, and participant behaviour.
Building decision-making "agents" to act autonomously in power markets.
Bringing an experimental mindset, prototyping and developing with the right model for the job.
We value diversity and our environment is supportive, challenging and focused on the consistent delivery of high quality, meaningful work. We encourage you to apply even if you do not meet every requirement in this posting.
Requirements:
You have exposure to energy markets or battery systems modelling.
You have a passion for time-series forecasting and experience bringing time-series forecasts to production.
You have experience with Bayesian or probabilistic modelling (e.g. Monte Carlo simulation, MCMC, PyMC, Hidden Markov Models, Stochastic Processes).
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 at least 3 years of commercial experience developing and productionising real-time projects in Machine Learning and Data Science.
You have a BA/BSc degree in Computer Science, Machine Learning, Applied Mathematics, Electrical Engineering, or related technical field.
You are comfortable with Agile software practices, version control (Git) and development environments (dev, test and production).
Extra credit if you can demonstrate:
MS or PhD degree in Computer Science, Machine Learning, or related technical field.
You have experience in Mathematical Optimization (e.g. convex optimization, mixed-integer linear programming, Cvxpy)
Knowledge of relational and/or non-relational databases (eg, SQL), and SQLAlchemy.
Full-stack / machine learning engineering experience.
AWS, terraform, continuous integration, monitoring and alerting.
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 Oxford.
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