51 to 75 of 116 scikit-learn Jobs in England

setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written More ❯

setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written More ❯

setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written More ❯

deep learning methods and machine 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 opportunities employer. We believe passionately More ❯

member. What We’re Looking For 2+ years’ experience as a Machine Learning Engineer, Data Scientist, or similar role. Strong background in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with building and deploying ML models into production. Knowledge of APIs, data pipelines, and cloud infrastructure (AWS, GCP, or Azure). Strong problem-solving skills and More ❯

member. What We’re Looking For 2+ years’ experience as a Machine Learning Engineer, Data Scientist, or similar role. Strong background in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with building and deploying ML models into production. Knowledge of APIs, data pipelines, and cloud infrastructure (AWS, GCP, or Azure). Strong problem-solving skills and More ❯

member. What We’re Looking For 2+ years’ experience as a Machine Learning Engineer, Data Scientist, or similar role. Strong background in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with building and deploying ML models into production. Knowledge of APIs, data pipelines, and cloud infrastructure (AWS, GCP, or Azure). Strong problem-solving skills and More ❯

member. What We’re Looking For 2+ years’ experience as a Machine Learning Engineer, Data Scientist, or similar role. Strong background in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with building and deploying ML models into production. Knowledge of APIs, data pipelines, and cloud infrastructure (AWS, GCP, or Azure). Strong problem-solving skills and More ❯

member. What We’re Looking For 2+ years’ experience as a Machine Learning Engineer, Data Scientist, or similar role. Strong background in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with building and deploying ML models into production. Knowledge of APIs, data pipelines, and cloud infrastructure (AWS, GCP, or Azure). Strong problem-solving skills and More ❯

machine learning lifecycle Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one More ❯

grow and shape the data science team and its role within the wider business. What We’re Looking For Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses (BigQuery, Snowflake, Redshift). Proven experience in deploying machine learning models or optimisation algorithms into More ❯

Experience building interactive dashboards and reporting tools. • Familiarity with data engineering, ETL processes, and data pipelines. • Experience with statistical modelling and machine learning techniques, and libraries such as scikit-learn, PyTorch, or TensorFlow. • Excellent communication skills able to explain complex analysis to non-technical stakeholders. • Proactive, inquisitive mindset with strong problem-solving skills. • Interest in cyber risk and More ❯

Experience building interactive dashboards and reporting tools. • Familiarity with data engineering, ETL processes, and data pipelines. • Experience with statistical modelling and machine learning techniques, and libraries such as scikit-learn, PyTorch, or TensorFlow. • Excellent communication skills—able to explain complex analysis to non-technical stakeholders. • Proactive, inquisitive mindset with strong problem-solving skills. • Interest in cyber risk and More ❯

in artificial intelligence and its application to drug discovery Understanding of ligand- and structure-based drug design. Experience with machine learning and major machine learning frameworks such as scikit-learn or PyTorch Proficiency in a low-level programming language such as C/C++ or Rust. Knowledge of advanced data analysis techniques such as multi-parameter optimization Open More ❯

s MLOps suite including Vertex Pipelines (or similar platforms). Technical Proficiency: in SQL and Python, along with familiarity with standard libraries used in data science such as scikit-learn, Keras, TensorFlow, pandas, NumPy, seaborn, and Matplotlib. Desirables: While not essential, the following experience would be highly beneficial: Production Experience with LLM Monitoring: Hands-on experience with monitoring More ❯

years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid understanding More ❯

years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid understanding More ❯

evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks More ❯

evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks More ❯

evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks More ❯

and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

years experience in Generative AI experience Proven experience with language-based Generative AI eg. LangChain, LangSmith, LangGraph, RAG, Proficiency in Python, data science libraries such as numpy, Pandas, scikit-learn Experienced in LLM frameworks such as LangChain Strong client-facing consulting or B2B experience Ability to build and create prototypes in a fast-paced environment BSc/MSc More ❯

building RAG pipelines, and experimenting with agentic AI workflows. Strong Python development skills and familiarity with modern ML and NLP frameworks and tooling (e.g. Hugging Face, spaCy, PyTorch, Scikit-learn). Familiarity with Kubernetes and infrastructure for deploying and scaling ML models is a plus. Exposure to systems integration challenges (e.g. connecting ML workflows with data stores like More ❯

algorithms, and frameworks . Proficiency in programming languages (Python, R, C/C++, Java) and secure coding practices. Hands-on experience with ML/LLM frameworks (TensorFlow, PyTorch, scikit-learn, etc.). Expertise in DevOps/CI/CD security and cloud-native architectures (containers, Kubernetes, Git). Strong knowledge of AI/ML-specific security vulnerabilities (adversarial More ❯