16 of 16 Remote Time Series Forecasting Jobs in London

Data Scientist – Energy Markets & Forecasting Location: London (Hybrid, 2–3 days per week) Compensation: £Competitive + Equity Sector: Climate Tech | Tier-1 VC Backed | Real-Time Systems I’m working with a cutting-edge climate tech startup that’s focused on decarbonising the energy grid. Backed by top-tier investors, they’re building technology that supports real-time energy trading and optimisation at scale. They’re looking for a Data Scientist with strong experience in time-series forecasting to design, build, and deploy real-time models that directly impact trading decisions. You’ll be working with complex, high-variance datasets and collaborating closely with traders, engineers, and product teams to turn data into … live insights that drive performance in fast-moving energy markets. Key Responsibilities: Develop and refine time-series forecasting models for energy trading and optimisation Work with real-time, high-volume data streams to deliver actionable insights Partner with traders, data scientists, and product engineers on live trading strategies Build and deploy production-ready ML models that More ❯

PhD) in Data Science, Machine Learning, Statistics, Computer Science, or related field. 5+ years of experience in data science roles, with proven expertise in: Machine learning (supervised/unsupervised), time series forecasting, deep learning. Programming in Python and SQL; proficiency with ML frameworks (TensorFlow, PyTorch, scikit-learn). Big data technologies and cloud platforms (AWS, Azure, or More ❯

PhD) in Data Science, Machine Learning, Statistics, Computer Science, or related field. 5+ years of experience in data science roles, with proven expertise in: Machine learning (supervised/unsupervised), time series forecasting, deep learning. Programming in Python and SQL; proficiency with ML frameworks (TensorFlow, PyTorch, scikit-learn). Big data technologies and cloud platforms (AWS, Azure, or More ❯

validate machine learning and statistical models for prediction, classification, clustering, or optimization. Apply supervised and unsupervised learning techniques using libraries such as Scikit-learn, TensorFlow, or PyTorch. Implement NLP, time-series forecasting, or optimization algorithms based on project requirements. Evaluate models using appropriate metrics and perform hyperparameter tuning for optimal performance. Convert proof-of-concept models into More ❯

foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and More ❯

foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and More ❯

Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI More ❯

data teams to ensure scalable solutions Requirements Extensive experience in data science, including applied statistics and machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP, AWS More ❯

presentations, and proposal delivery. Skills and Experience Required Strong capabilities across a range of AI techniques, including supervised and unsupervised learning, generative AI, deep learning, graph analytics, statistical modelling, time-series forecasting, geospatial analysis, NLP, sentiment analysis, and pattern detection. Excellent communication skills, with the ability to present complex technical concepts clearly and confidently to non-technical More ❯

presentations, and proposal delivery. Skills and Experience Required Strong capabilities across a range of AI techniques, including supervised and unsupervised learning, generative AI, deep learning, graph analytics, statistical modelling, time-series forecasting, geospatial analysis, NLP, sentiment analysis, and pattern detection. Excellent communication skills, with the ability to present complex technical concepts clearly and confidently to non-technical More ❯

owner of these integrations. - Optimize AI Pipelines: Ensure our AI pipeline works like clockwork. Improve and support its complex infrastructure. - ML Experience: Practical experience with ML, including classification, clustering, time series forecasting, and anomaly detection. You need to know the concept and be handly with the most common libraries - Model Hosting and Monitoring: Host and monitor NLP … models and LLM for real-time and batch inference. - Develop Monitoring Systems: Create and support robust models for monitoring. - Support and Innovate: Assist with a long tail of super important tasks, bringing innovative solutions to the table. Qualifications: - Python Proficiency: Strong Python skills with experience in building and monitoring production services or APIs. Experience with third-party APIs is … and social media into a single, easily accessible space. This enables companies like Grubhub, OpenAI, Dropbox, and Careem to collect and derive actionable insights and deliver a better, real-time customer experience that drives sustainable growth. We are backed by top investors, including Neo, Sukna, Race Capital, Propeller, and Wamda, having raised $12m to date More ❯

owner of these integrations. - Optimize AI Pipelines: Ensure our AI pipeline works like clockwork. Improve and support its complex infrastructure. - ML Experience: Practical experience with ML, including classification, clustering, time series forecasting, and anomaly detection. You need to know the concept and be handly with the most common libraries - Model Hosting and Monitoring: Host and monitor NLP … models and LLM for real-time and batch inference. - Develop Monitoring Systems: Create and support robust models for monitoring. - Support and Innovate: Assist with a long tail of super important tasks, bringing innovative solutions to the table. Qualifications: - Python Proficiency: Strong Python skills with experience in building and monitoring production services or APIs. Experience with third-party APIs is … and social media into a single, easily accessible space. This enables companies like Grubhub, OpenAI, Dropbox, and Careem to collect and derive actionable insights and deliver a better, real-time customer experience that drives sustainable growth. We are backed by top investors, including Neo, Sukna, Race Capital, Propeller, and Wamda, having raised $12m to date More ❯

enterprise clients) to identify opportunities, translate needs into scalable AI solutions, and bring models into production. What You’ll Do Design and deploy AI systems across areas like personalisation, forecasting, and information retrieval Build and maintain robust data pipelines, model training workflows, and monitoring systems Collaborate cross-functionally to apply ML/AI to real-world business problems Develop … Willingness to travel occasionally for in-person collaboration or client work Nice to Have Experience with retrieval-augmented generation (RAG) or foundation models Exposure to NLP, recommendation systems, or time series forecasting Familiarity with streaming architectures and experimentation platforms Understanding of healthcare data standards (HIPAA, FHIR) Interest in ethical AI and explainability More ❯

enterprise clients) to identify opportunities, translate needs into scalable AI solutions, and bring models into production. What You’ll Do Design and deploy AI systems across areas like personalisation, forecasting, and information retrieval Build and maintain robust data pipelines, model training workflows, and monitoring systems Collaborate cross-functionally to apply ML/AI to real-world business problems Develop … Willingness to travel occasionally for in-person collaboration or client work Nice to Have Experience with retrieval-augmented generation (RAG) or foundation models Exposure to NLP, recommendation systems, or time series forecasting Familiarity with streaming architectures and experimentation platforms Understanding of healthcare data standards (HIPAA, FHIR) Interest in ethical AI and explainability More ❯

. Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and More ❯

Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as … well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Machine Learning Engineer, timeseries, forecasting, VertexAI, GCP Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications from people of all More ❯