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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Habitat Energy - **Location:** Oxford, UK - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Programming, Python (Programming Language), PostgreSQL, NumPy, Package Management Systems, SciPy, SQLAlchemy, Grafana, Virtual Environment, Scikit Learn, Kubernetes, Xgboost, Plotly, Claude, Streamlit Framework - **Published:** October 2, 2026 - **Apply:** https://startup.jobs/data-scientist-habitat-energy-10263665 ## About the Role Preferred Technical Skills * Time-series modelling (ARIMA, SARIMA, etc.) and - Tree-based & gradient boosting models (XGBoost, LightGBM, NGBoost) * Expertise/knowledge of internally stored data & data consumers as well as other data sources that are currently not databased * Python (3+ for production level code, including pydantic, liniting, type hinting etc) * Dashboard building (Grafana, Streamlit, Superset, Plotly Dash etc), * Awareness of the drivers of PnL, trade life cycle and associated cashflows in an energy trading and asset optimisation business * Genuine interest in energy markets and renewable energy solutions Communication, Presentation and Soft Skills: * Excellent data organisation, visualisation, story telling, prioritisation of messaging and persuasion of stakeholders * Adaptability to work in a dynamic, fast-paced trading environment. * Self-starter/strong initiative with the ability to manage multiple tasks and deadlines. * Strong presentation skills and the ability to communicate effectively with technical and non-technical audiences. Optimisation Skills; to further bolster and work with our existing optimisation function and Electricity Trading exeperience, especially associated with BESS will elevate your application for this role: * Simulation-Optimization Integration * Stochastic Programming & Robust Optimization * Virtual environments and package management (poetry/uv) * Awareness of battery storage technology, including operational characteristics and revenue opportunities. * Flexibility & Battery Storage (BESS) Revenue Stacking * Renewable Energy Generation, operations and monetisation (especially solar) * Energy Storage trading Experience ## Description This vacancy is for an Applied Data Scientist, will play a critical role in driving the success of our battery storage trading operations across wholesale markets (including day-ahead and intraday), Balancing Mechanism (BM), and ancillary service markets (frequency response and reserve services). You will work with analysts from the Applied Analytics team, and traders from the business to develop market forecasts to improve revenue capture for the batteries under our optimisation, support their productionisation and regularly discuss insights, improvements and conclusions with the rest of the Applied Analytics team and Trading Team. You will be responsible for: * Developing market forecasts for our trading teams, who trade the wholesale electricity and ancillary service markets in GB * Building, prototyping, testing, and scaling parallelised predictive models to forecast electricity market prices, volumes and value across wholesale and ancillary markets * Cleaning complex datasets, engineering high-value temporal features, and accounting for complex nuances in the electricity market * Creating actionable insights to improve real world trading performance to maximise revenue and manage risk, going beyond just monitoring model accuracy metrics * Contributing both ad hoc insights and enduring intelligence to inform trading strategies * Creating applications to automate the way the batteries we optimise are traded * Creating insights into risk so traders can understand the range of outcomes of decisions * Visualising and communicating insights to make it easy for users to assimilate large quantities of insights and quickly make high reward vs risk decisions * Becoming a specialist on specific areas of the markets we are active in and providing support to colleagues on this topics * Working with tech teams to source data to underpin your work and help them productionise your applications, * Requirements/Request elicitation and logging (e.g. understanding user needs for models/analysis/outputs etc) * Scoping of technical work * Functional prototyping (pre-productionised apps hosted locally or on dev/staging) * Creating and maintaining documentation to accompany codebases e.g. explanatory methodologies * Interfacing with technical teams (technical literacy to collaborate smoothly with Core Engineering / Applied Engineering) to support productionisation, * Programming: Python, polars, pydantic, uv, SQLAlchemy, Streamlit * Infrastructure and DB: Postgres, Warehousing (if we did it), prefect, Kubernetes, SQLAlchemy, AWS * Visualisation: Grafana, Superset, Marimo * Forecasting + general DS: lightgbm, xgboost, numpy, scipy, scikit-learn * Claude AI Ultimately we are looking for someone who is a great fit for our company so we encourage you to apply even if you may not meet every requirement in this posting. 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