1 to 25 of 380 Remote scikit-learn Jobs in the UK

Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience More ❯

Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience More ❯

techniques, including LLMs, GenAI, and automated AI systems. • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). • Proficiency in Python, R, or other relevant programming languages. • Proficiency in working with large datasets, data wrangling, and data preprocessing. • Experience in More ❯

and finance/savings data (transaction flows, compliance, user segmentation, etc.) Technical Skills: Proficient in Python, SQL, and data science libraries (Pandas, NumPy, Scikit-learn, Hugging Face Transformers) Familiarity with embedding models, vector databases (e.g., Pinecone, FAISS, Weaviate) Experience with cloud platforms (AWS, GCP, or Azure) and MLOps More ❯

methods (SHAP, LIME) and adopt best practices for responsible AI. Qualifications Technical Skills Programming: Python (NumPy, Pandas), R, SQL. ML/DL Frameworks: Scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers. Big Data & Cloud: Databricks, Azure ML, AWS SageMaker, GCP Vertex AI. Automation: MLflow, Kubeflow, Weights & Biases for experiment More ❯

C, Julia, C++, or similar. • Strong proficiency in Python and its scientific computing/ML ecosystem (e.g., NumPy, Pandas, TensorFlow, AI Foundry, OpenAI, Scikit-learn etc.). • Solid understanding of core machine learning concepts • Hands-on experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch More ❯

Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally More ❯

software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience More ❯

software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience More ❯

Good working knowledge of Python Implementing end-to-end ML pipelines Hand-on experience in Python data science ecosystem (e.g. numpy, scipy, pandas, scikit-learn, matplotlib etc.) Deep Learning frameworks (TensorFlow, PyTorch, MLX) Popular classification and regression techniques Unsupervised learning & matrix factorisation algorithms Natural Language Processing (NLP) and More ❯

experience Proven track record of delivering AI solutions for complex scientific problems Experience with machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn, spaCY), and data processing techniques. Demonstrated experience in developing and deploying machine learning models in production environments. Experience with AI Cloud Platforms (AWS More ❯

are searching for are: style="margin-bottom:0.0in;margin-top:0.0px;text-align:justify"- -Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache More ❯

or causal inference Proficiency in Python for data analysis and statistical modeling (pandas, numpy, scipy, statsmodels) Familiarity with machine learning libraries such as scikit-learn Experience with SQL for data extraction and manipulation Demonstrated ability to translate analytical findings into business recommendations Track record of successful project delivery More ❯

and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated ability to More ❯

and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated ability to More ❯

production ready code, architect packages, and make sound architectural and procedural choices for effective shared codebases Python and scientific computing packages (Pytorch, Numpy, Scikit-learn, TensorFlow) Database technologies such as ElasticSearch, Neo4j, and SQL Excellent interpersonal, verbal, and written communication skills A flexible attitude with respect to work More ❯

life science organization is considered an asset. Other skills we are searching for are: Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache More ❯

equivalent qualification, or other evidence of equivalent knowledge. Professional or research experience in some of the following: ML/NLP tools like PyTorch, Scikit-learn, Transformer architecture and Neural Networks. Coding and software engineering in mainstream programming languages, such as Python. Statistical packages for data manipulation and in More ❯

in data science, machine learning, or a related role Proficiency in programming languages such as Python or R, and libraries like TensorFlow, PyTorch, Scikit-learn, or Pandas Strong understanding of statistical modeling, probability, and optimization techniques Ability to work with messy, real-world datasets and perform feature engineering More ❯

equivalent qualification, or other evidence of equivalent knowledge. Professional or research experience in some of the following: ML/NLP tools like PyTorch, Scikit-learn, Transformer architecture, and Neural Networks. Coding and software engineering in mainstream programming languages, such as Python. Statistical packages for data manipulation and in More ❯

we’re a flat, fast-moving team What You’ll Bring to the team Strong Python skills and experience with ML frameworks like scikit-learn, TensorFlow, PyTorch, Hugging Face Solid grasp of data wrangling , feature engineering , and model evaluation techniques Proficiency in designing and deploying production-ready ML More ❯

Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally More ❯

Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally More ❯

experience of large-scale data analysis and hypothesis testing. • Strong proficiency in statistical analysis and predictive modeling. • Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. • Excellent problem-solving skills and attention to detail. • Strong communication skills with the ability to More ❯

experience of large-scale data analysis and hypothesis testing. • Strong proficiency in statistical analysis and predictive modeling. • Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. • Excellent problem-solving skills and attention to detail. • Strong communication skills with the ability to More ❯