16 of 16 Remote NumPy Jobs in the UK excluding London

for analyzing and interpreting large datasets. Ability to apply statistical techniques to validate models and algorithms. Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity: Generous equity package, on a More ❯

a highly numerate subject (e.g. computer science, engineering, mathematics, or data science). Minimum 2 years' experience in Python development, including use of scientific and data libraries such as NumPy, pandas, SciPy, or PySpark. Experience working with machine learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, or similar. Strong grasp of object-oriented software engineering principles, with a More ❯

a highly numerate subject (e.g. computer science, engineering, mathematics, or data science). Minimum 2 years' experience in Python development, including use of scientific and data libraries such as NumPy, pandas, SciPy, or PySpark. Experience working with machine learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, or similar. Strong grasp of object-oriented software engineering principles, with a More ❯

of Bedrock, Sagemaker, Python and Pandas. Key Responsibilities: * Working experience LLMs under Bedrock and Sagemaker both Amazon * Python with APIs to ChatGPT * Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Key Skills & Experience: AWS Data Science Environment: Hands-on experience with Sage Maker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline orchestration … Use-Case Development: Proficiency with Amazon Tex-tract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rule Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Writing clean, modular, and testable code. Traditional Machine Learning Models: Experience with regression (linear, ridge), classification (logistic regression, decision trees, random forests), clustering More ❯

with LLM/GenAI prompting and augmentation for textual analysis, with an interest in learning more. Experience working with commonly used data science libraries and frameworks, e.g. Spacy, pandas, numpy, scikit-learn, Keras/TensorFlow, PyTorch, LangChain, Huggingface transformers etc. Familiar with both on-premises and cloud-based platforms (e.g. AWS). Working understanding of ML Ops workflows and ability More ❯

Are you looking for a career move that will put you at the heart of a global financial institution? Then bring your skills in Python Development to join our growing Market Risk Technology Team. The Market Risk Technology teanis seeking More ❯

Machine Learning Engineer - SaaS - London (Tech stack: Machine Learning Engineer, Python, TensorFlow, PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) We have several exciting … training will be provided to fill any gaps in your skill set): Machine Learning Engineer, Python, TensorFlow, PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network More ❯

contribute fresh ideas to the team. Skills and Experience: Degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Proficiency in Python and key libraries such as NumPy, Pandas, scikit-learn, TensorFlow or PyTorch. Basic understanding of machine learning algorithms and model evaluation techniques. Strong analytical and communication skills. Comfortable working in a collaborative environment and taking feedback. More ❯

experience in designing, developing & deploying scalable backend systems. Familiarity with CICD, containerisation, deployment technologies & cloud platforms (Jenkins, Kubernetes, Docker, AWS) or Familiarity with Big Data and Machine Learning technologies (NumPy, PyTorch, TensorFlow, Spark). Excellent communication, collaboration & problem solving skills, ideally with some experience in agile ways of working. Security clearance: You must be able to gain and maintain the More ❯

deadlines whilst remaining organised Strong analytical approach to problems Technical skills: Proficiency in Python Proficiency with version control (Git) Familiarity with containerisation (Docker) Familiarity with data processing tools (Pandas, NumPy) Experience using machine learning frameworks like PyTorch or TensorFlow Familiarity with cloud platforms and their ML services Benefits: MOST IMPORTANT: Your career Mentorship from senior machine learning engineers Access to More ❯

deadlines whilst remaining organised Strong analytical approach to problems Technical skills: Excellence with Python Excellence with version control (Git) Proficiency with containerisation (Docker) Proficiency with data processing tools (Pandas, NumPy) Experience using machine learning frameworks like PyTorch or TensorFlow Familiarity with cloud platforms and their ML services Benefits: MOST IMPORTANT: Your career Mentorship from senior machine learning engineers and data More ❯

proactive approach to problem-solving and collaboration, with the ability to work closely with technical and non-technical teams. Desired Skills Python expertise, especially with data libraries like Pandas, NumPy, and Scikit-learn. Familiarity with ETL tools and data pipeline orchestration. Exposure to data science tools like SAS or Posit. Experience in performance-critical environments, particularly with large-scale data More ❯

key product and business metrics The Person Experience in a data/product/business analyst role (ideally in tech or SaaS) Strong SQL and Python skills (e.g. Pandas, NumPy) and confidence handling large, complex datasets Proficiency with BI tools (e.g. Tableau, Looker, Metabase) Excellent communication and data storytelling skills Comfortable working cross-functionally with technical and commercial teams A More ❯

XLOOKUP, macros) Experience with Power BI/Fabric Strong problem-solving and critical thinking abilities Excellent communication skills and stakeholder engagement experience Familiarity with Python for data analysis (pandas, NumPy, etc.) - desirable Understanding of data warehousing, ETL, and data governance - desirable Degree in a STEM subject - nice to have Knowledge of the energy/utilities sector - a bonus Benefits include More ❯

Expertise: Prior experience in anomaly detection applied to areas such as QA, gameplay analysis, computer vision or video stream analysis. Proven experience with machine learning frameworks such as Python, NumPy, TensorFlow, or PyTorch. Strong understanding of data analysis, signal processing, and statistical modeling. Experience with video processing and understanding of game streaming technologies is a plus. Problem-Solving Skills: Excellent More ❯

Expertise: Prior experience in anomaly detection applied to areas such as QA, gameplay analysis, computer vision or video stream analysis. Proven experience with machine learning frameworks such as Python, NumPy, TensorFlow, or PyTorch. Strong understanding of data analysis, signal processing, and statistical modeling. Experience with video processing and understanding of game streaming technologies is a plus. Problem-Solving Skills: Excellent More ❯