76 to 100 of 277 scikit-learn Jobs in England

Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with More ❯

Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with More ❯

in industry. Demonstrable industry experience delivering AI/ML frameworks for a product. Expertise in working with ML frameworks such as PyTorch, Tensorflow, scikit-learn, Langchain. Experience with DL architectures such as transformers/CNNs. Excellent programming skills in Python and object-oriented paradigm. Agile software development experience. More ❯

in industry. Demonstrable industry experience delivering AI/ML frameworks for a product. Expertise in working with ML frameworks such as PyTorch, Tensorflow, scikit-learn, Langchain. Experience with DL architectures such as transformers/CNNs. Excellent programming skills in Python and object-oriented paradigm. Agile software development experience. More ❯

MLOps tools and practices (e.g., Docker, CI/CD pipelines, monitoring frameworks). Strong proficiency in Python and libraries like Pandas, NumPy, and scikit-learn, with familiarity in frameworks like TensorFlow or PyTorch being a plus Cloud experience—AWS preferred - including deploying and managing models in cloud environments More ❯

MLOps tools and practices (e.g., Docker, CI/CD pipelines, monitoring frameworks). Strong proficiency in Python and libraries like Pandas, NumPy, and scikit-learn, with familiarity in frameworks like TensorFlow or PyTorch being a plus Cloud experience—AWS preferred - including deploying and managing models in cloud environments More ❯

learning Experience in building machine learning models for business application Experience in applied research PREFERRED QUALIFICATIONS Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. PhD Amazon is an equal More ❯

all domains: data pre-processing and post-processing, machine learning, deep learning, time-series algorithms, explainability methods and more, using Python packages (including Scikit-Learn, Pandas, NumPy, NLTK, etc.). Preferred skills and technical familiarity At least 4 years of proven experience in Data Science. Sc./M.Sc. More ❯

with a blend of some of the following skills: Machine learning techniques - including supervised and unsupervised methods and model evaluation. Key libraries including scikit-learn, scipy, pandas, and numpy (or equivalents). Data preprocessing - working with large untidy datasets and the ability to clean and transform data in More ❯

Proficient in financial analysis, modelling, and statistics, with experience extracting insights from heterogeneous multi-dimensional datasets. Ability to apply machine learning techniques (e.g., scikit-learn, PyTorch, TensorFlow) and present complex data visually using Matplotlib, seaborn, or Streamlit. Fluent in Python, with experience working with data processing libraries such More ❯

Bayesian models, Markov chains and multivariate time-series modelling. Experience with widely used probabilistic programming and machine learning libraries such as Stan, PyMC3, Scikit-Learn, Keras, Tensorflow or PyTorch. Exposure to cloud computing, ideally AWS. An interest in sports betting. More ❯

data science or machine learning roles. Strong knowledge of behaviour biometrics or sensor-based or time series data Solid Python skills (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch). Experience with time-series data or sensor-based or behavioural biometric data, and sequential modelling (e.g., LSTMs, Transformers). More ❯

data or commercial experience is a plus Strong understanding of mathematical background, focusing on statistics and linear algebra Highly proficient in Python (Pandas, Scikit-Learn, PyTorch, PySpark) and SQL Experience with Snowflake (function & procedure) and Snowpark is a plus Experience with unit and integration tests Strong understanding of More ❯

data visualization tools (e.g., Tableau, Power BI, matplotlib) and cloud platforms (preferably AWS). Expertise in statistics and machine learning frameworks (e.g., PyTorch, scikit-learn). Familiarity with Git and collaborative workflows, such as pull requests and code reviews. Experience in product experimentation, including A/B testing. More ❯

. Experience in Data Lake technologies (DataBricks) and/or Dataiku. Experience with Data Science and AI tools and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Knowledge of machine learning algorithms, statistical modelling, and AI-driven analytics. Data analysis, management, and visualisation expertise. Proactively manages conflicts within their More ❯

management within the Generative AI space, including LLMOps. Comprehensive understanding of machine learning and NLP algorithms, with hands-on experience in frameworks like Scikit-Learn, TensorFlow, and PyTorch. Strong knowledge of generative AI techniques, including deep generative models, auto regressive models, and reinforcement learning for generative tasks. More ❯

management within the Generative AI space, including LLMOps. Comprehensive understanding of machine learning and NLP algorithms, with hands-on experience in frameworks like Scikit-Learn, TensorFlow, and PyTorch. Strong knowledge of generative AI techniques, including deep generative models, auto regressive models, and reinforcement learning for generative tasks. #J More ❯

SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and More ❯

SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and More ❯

learning Experience in building machine learning models for business application Experience in applied research PREFERRED QUALIFICATIONS Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. More ❯

algorithms applied to computer vision challenges Knowledgeable about key architectures like Vision Transformers, DeepLabv3, and SegFormer Proficient in Python and ML tools, including Scikit-Learn, NumPy, Pandas, PyTorch, TensorFlow, or Keras Capable of applying machine learning to solve real-world problems Please apply via the link for immediate More ❯

algorithms applied to computer vision challenges Knowledgeable about key architectures like Vision Transformers, DeepLabv3, and SegFormer Proficient in Python and ML tools, including Scikit-Learn, NumPy, Pandas, PyTorch, TensorFlow, or Keras Capable of applying machine learning to solve real-world problems Please apply via the link for immediate More ❯

the business. Requirements: 4+ years of experience in Data Science, with a strong focus on AWS cloud solutions. Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) and SQL . Hands-on experience with AWS services (SageMaker, Lambda, Glue, Redshift, Athena, S3). Strong understanding of ML model More ❯

skills in regression analysis, classification, clustering, and other relevant techniques. Programming skills in Python and R, with experience in data science libraries (eg, scikit-learn, pandas, TensorFlow) for data manipulation, analysis, and model development. Experience with data visualisation tools (eg, Tableau, Power BI) to communicate data insights effectively. More ❯

skills in regression analysis, classification, clustering, and other relevant techniques. Programming skills in Python and R, with experience in data science libraries (eg, scikit-learn, pandas, TensorFlow) for data manipulation, analysis, and model development. Experience with data visualisation tools (eg, Tableau, Power BI) to communicate data insights effectively. More ❯