101 to 125 of 209 scikit-learn Jobs in England

multiple domains (NLP, vision, audio, time series, tabular data). Proficient in Python and relevant ML/data science libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Experience with cloud-based model deployment (AWS) and ML engineering best practices. Excellent communication, problem-solving, and project delivery skills. ...

memory management. Experience with widely used tools in data science and machine learning. Developers should be somewhat familiar with libraries like NumPy, pandas, scikit-learn, and PyTorch. Proficiency in testing approaches and frameworks like pytest as well as automation tools like Github Actions or Travis CI for maintaining ...

development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training ...

development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training ...

Ph.D. preferred). Proficiency in programming languages, particularly Python, R, or SQL. Experience with machine learning techniques and frameworks (e.g., TensorFlow, Scikit-learn). Strong analytical skills with a knack for problem-solving and critical thinking. Excellent communication skills, with the ability to explain complex concepts ...

academic background (Bachelor’s degree 2:1 or above in a quantitative subject). Strong Python skills and experience with ML frameworks (e.g. scikit-learn, TensorFlow, PyTorch). Experience with model deployment, monitoring and ML pipelines (e.g. CI/CD, MLOps concepts). A collaborative mindset with strong ...

stack High quality production code in Python . Libraries such as NetworkX , TensorFlow or PyTorch , NLTK, spaCy, Hugging Face, BERT , Pandas, NumPy, scikit learn . Graph based ML familiarity: link prediction, anomaly detection, traversal, community detection. NLP/NLU skills: entity/relation recognition, summarisation, topic modelling, classification ...

marketing, pricing, and promotional levers, and how they influence commercial performance. Solid Python skills for data manipulation, modelling, and visualisation (e.g., pandas, NumPy, scikit-learn). High proficiency with Microsoft Office, particularly Excel, PowerPoint, and Word. Exceptional attention to detail and a commitment to analytical rigour. Ability ...

marketing, pricing, and promotional levers, and how they influence commercial performance. Solid Python skills for data manipulation, modelling, and visualisation (e.g., pandas, NumPy, scikit-learn). High proficiency with Microsoft Office, particularly Excel, PowerPoint, and Word. Exceptional attention to detail and a commitment to analytical rigour. Ability ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...

trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components ...