1 to 25 of 39 NumPy Jobs in the UK excluding London

including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Strong skills in data preprocessing, wrangling, and augmentation techniques Experience deploying More ❯

data science, or a closely related field Strong understanding of macroeconomics, financial markets, and investment principles Proficiency in Python, with experience in data manipulation libraries such as pandas and NumPy Strong analytical skills with the ability to design efficient data pipelines and workflows Excellent communication skills, able to convey complex concepts to both technical and non-technical stakeholders Preferred Qualifications More ❯

data science, or a closely related field Strong understanding of macroeconomics, financial markets, and investment principles Proficiency in Python, with experience in data manipulation libraries such as pandas and NumPy Strong analytical skills with the ability to design efficient data pipelines and workflows Excellent communication skills, able to convey complex concepts to both technical and non-technical stakeholders Preferred Qualifications More ❯

data science, or a closely related field Strong understanding of macroeconomics, financial markets, and investment principles Proficiency in Python, with experience in data manipulation libraries such as pandas and NumPy Strong analytical skills with the ability to design efficient data pipelines and workflows Excellent communication skills, able to convey complex concepts to both technical and non-technical stakeholders Preferred Qualifications More ❯

with the ability to write ad-hoc and complex queries to perform data analysis. Experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc. You will be able to develop solutions in a hybrid data environment (on-Prem and Cloud). Hands on experience with developing data pipelines for structured, semi-structured More ❯

ensuring reliability and accuracy. Stay up-to-date with the latest ML research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with More ❯

computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working More ❯

computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working More ❯

computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working More ❯

AI/ML algorithms and techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model More ❯

AI/ML algorithms and techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model More ❯

AI/ML algorithms and techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model More ❯

structured and unstructured datasets of varying sizes. Track record of implementing impactful models that drive sustained business results. Proficiency in the Python data science tech stack (pandas, scikit-learn, NumPy, and visualisation libraries) Experience working in a Linux-based cloud environment (e.g. GCP, Azure, AWS). Experience using git version control. Communication, stakeholder management, and problem-solving skills are critical. More ❯

Role Requirements 2-4 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. More ❯

evaluation Requirements: 3+ years of experience in data science or ML, ideally in biotech or healthcare Strong Python programming skills and experience with ML libraries Familiarity with Jupyter , Pandas , NumPy , and MLFlow Experience working with clinical or biological datasets is a big plus Comfortable working in a fast-paced, research-driven environment Bonus Skills: Knowledge of genomics , bioinformatics , or clinical More ❯

commercial data analysis role 📊 Strong technical skills in SQL Strong dashboard and data viz skills in PowerBI and DAX Strong statistical analytics experience in Python and associated libraries PANDAS, NumPy, SciPy etc. 🐍 Automate when you should with Power Platform and other tools Experience engaging with stakeholders 🗣️ Ability to interrogate data, find trends, anomalies and leverage this data to make suggestions More ❯

or Master’s degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency More ❯

or Master’s degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency More ❯

similar domains with forecasting needs. Skills and competencies Essential: Experience working with Python or R in a production or research 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. More ❯

similar domains with forecasting needs. Skills and competencies Essential: Experience working with Python or R in a production or research 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. More ❯

similar domains with forecasting needs. Skills and competencies Essential: Experience working with Python or R in a production or research 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. More ❯

ideally within a commercial or trading environment Proficiency in time series analysis, regression modelling, and forecasting techniques Strong experience with Python and core libraries for data science (e.g., pandas, NumPy, scikit-learn, statsmodels) Ability to manipulate and analyse large, complex datasets with attention to detail Clear, confident communicator who can explain analytics and influence commercial decisions Experience using visualisation tools More ❯

testing pipelines and 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 More ❯

code quality, documentation, 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 More ❯

Data Analysis, with approx. 4+ years in a senior or equivalent role. Strong experience in SQL (writing and optimising complex queries). Proficiency in Python (including libraries like Pandas, NumPy, SQLAlchemy). Experience working with large datasets , and advanced data modelling techniques. Ability to engage with stakeholders and translate their needs into actionable data solutions. Solid understanding of data structures More ❯