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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Volter - **Location:** London, UK - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Extract Transform Load (ETL), Python (Programming Language), NumPy, SQL Databases, Pytorch, Pandas, Scikit Learn, Statistics Packages, Xgboost, Machine Learning Operations, Terraform - **Published:** September 17, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=b337418a1d336fca ## About the Role * 4-8+ years in Data Science/ML with a focus on time-series forecasting and decision analytics * Strong Python (pandas, NumPy, scikit-learn, statsmodels; PyTorch/TF a plus) and SQL; rigorous evaluation (MAE/RMSE, MAPE, pinball loss) * Experience productionising models (APIs/batch jobs), experiment tracking (e.g., MLflow) and basic MLOps * Being able to evaluate the right tools for the job given business requirements & experiment with new ways of doing things to continuously improve * Comfort combining statistical baselines with ML methods (gradient boosting, GLMs, probabilistic models) We need a hands-on lead who can ship useful forecasts and iterate quickly without a big platform team. Energy experience accelerates you, but we'll value evidence that you can master domain context fast and build pragmatic, explainable models that survive contact with production. Stand-out candidates will have experience in… * GB energy markets (half-hourly settlement, weather-driven load, network tariffs) and portfolio risk analytics * Experience with AWS and infrastructure (eg Terraform) * Experience and willingness to surface insights in relevant UIs/products * Forecast explainability, uncertainty quantification and decision tooling for non-technical users * Optimisation (LP/MIP) for hedging or tariff design, * Curious, pragmatic and outcome-driven. * You love shipping models that make decisions better today rather than making them better tomorrow. * You are energised by early-stage businesses, are adaptable and thrive within startup environments. * You have a strong bias toward action and having an impact quickly. You want to get sht done. * You are a self-starter and autonomous in your way of working, but ultimately believe a team can get further together than any individual. * You communicate clearly and keep things as simple as possible., * A dynamic and fast-changing environment with incredible responsibility and autonomy * Working directly with and learning from experienced startup founders who've invested in and scaled businesses up to several billion dollars in valuation * The ability to build and own something from the very beginning * Working on market-leading and genuinely impactful products that help solve the climate crisis * A kick-ass team of colleagues * We value in person time at our office in London but offer hybrid/flexible working ## Description You'll lead our data science work, including owning forecasting and pricing optimisation: producing accurate half-hourly demand and generation forecasts, shaping prices, quantifying uncertainty and translating it into simple decisions for customers and our supply portfolio. You'll own the full model lifecycle-from problem framing and baselines to productionisation, monitoring and iterative improvement. You are a self-starter who excels both independently and in a team. You dislike corporate structure and bureaucracy, and believe in a "best idea wins" culture. This is why you prefer a growth-oriented, flat, startup environment. A desire to keep learning and having an impact is very important to you. You fear looking back in 10 years time and realising you never made a difference…that you were simply a tiny cog in a large machine that will churn on with or without you. ️ Day-to-day responsibilities * Build, validate and deploy time-series models (including probabilistic where useful) and matching optimisation algorithms for customer demand and generation and constantly improve model performance * Understand customer profiles and develop relevant features from HHD, weather, calendar and price inputs; set up robust back-tests and error attribution * Develop, maintain and improve pricing and trading decision engines to maximise PnL * Alongside engineering, create reliable feature/data ETL pipelines, and partner with product to surface insights in the platform * Create risk and hedging analytics (e.g., shape/volume error distributions, scenario analysis, what-if tools) * Design monitoring for model/data drift; manage model registries and experiment tracking * Be responsible for driving new initiatives to improve business outcomes from a data science perspective and be able to drive and own from idea to scoping, production and maintaining * Communicate results clearly to non-technical stakeholders; build explainability into outputs ## Related Videos - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Vectorize all the things! 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