1 to 25 of 51 Permanent NumPy Jobs in London

Physics, or related); Master's degree preferred. Professional software development experience, with deep expertise in Python and its data/engineering ecosystem (e.g., pandas, NumPy, FastAPI, orchestration tools). Proven track record of delivering production-grade automation, data pipelines, or testing frameworks in a complex enterprise environment; financial services experience ...

Experience of cloud platforms (AWS, Azure, or GCP) Experience of containerisation (Docker) and orchestration (Kubernetes) Exposure to data engineering tools/libraries (e.g. Pandas, NumPy) or NLP libraries Knowledge of message queues/event-driven architecture (e.g. RabbitMQ, Kafka) Understanding of CI/CD tools (e.g. Jenkins, GitHub Actions, Azure ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

experience, and a passion for building scalable, high-quality ML and data solutions in production environments. Essential Experience Strong programming skills in Python (Pandas, NumPy, etc.). Proficiency in SQL for data querying and transformation. Hands-on experience with Machine Learning techniques and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). ...

What We’re Looking For: Essential Skills & Experience Proven experience solving complex, real-world problems using data science and analytics Strong Python skills (pandas, numpy, scikit-learn) with a solid grounding in probability and statistics Deep understanding of machine learning methods and their practical application Experience delivering multiple ...

engineering skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

design and software engineering fundamentals: version control, code review, automated testing, dependency and environment management. Machine learning across the standard toolkit (scikit learn, pandas, NumPy, statsmodels or equivalents), with sound judgement about model selection, validation and the limits of what the data supports. MLOps and CI/CD in practice ...

translate business problems into measurable analytical outcomes.* Experience taking models from development into production environments.### Technical Skills* Python and associated data science ecosystem (Pandas, NumPy, Scikit-learn).* Machine learning techniques including classification, regression, clustering and anomaly detection.* Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. ...

engineering skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with ...

sequential modeling Excellent communication skills with the ability to communicate concepts clearly and precisely Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES Experience as a Data Architect or Senior Manager Proven track ...

infrastructure, such as: data pre- and post-processing, sampling and curation, ablation studies, evaluation Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) database; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES 5+ years experience in data science or related areas 2+ ...

architecture deployed at scale on Kubernetes. The rest of the tech stack includes Django REST Framework, FastAPI, PostgreSQL, AWS, React.js, Docker, Redis, Celery, Pandas, NumPy, Git, Jenkins, and Elasticsearch. We put significant emphasis on design patterns, code readability, automated testing, maintainability, and extensibility. As Software Architect ...

cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP); building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; C/C++ for computer vision, geometry processing, or scientific computing; software engineering concepts and best ...

across domains such as NLP, computer vision, audio, graphs, time-series or tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying ...

area such as predictive modelling, classification, regression, optimisation or recommendation systems Strong proficiency in Python and open-source data libraries such as Pandas, NumPy and Scikit-learn A solid grounding in statistical methodologies, along with data extraction, manipulation and feature engineering techniques Experience with Spark, agile delivery methods ...

predictive modelling, forecasting and/or optimisation - with strong command of the underlying statistical principles Strong proficiency in Python and core ML libraries (e.g., NumPy, Pandas, Scikit-Learn, xgboost, shap) Advanced working knowledge of SQL Hands‐on experience with data pipelines and ML infrastructure Experience working within AWS (ideally using ...

improve reliability and speed of accessing our wide data ecosystem. We run a variety of time consuming ETL tasks using libraries such as NumPy, Scikit-learn, Pandas, and view/tables from a variety of relational databases. The aim is to integrate and transition all to a single data warehouse ...

roles, not just in theory We're looking for: Strong hands-on AI/ML and Data Science expertise (Python essential — NumPy, Pandas, Scikit-learn; exposure to PyTorch, TensorFlow, LangGraph or similar a plus) Proven experience delivering technical training to a mix of technical and non-technical audiences, virtually ...