1 to 25 of 35 Permanent scikit-learn Jobs in the UK excluding London

data science. Requirements 5+ years of experience in data science, machine learning, or AI model development. Expertise in Python, R, or Julia, with proficiency in pandas, NumPy, SciPy, scikit-learn, TensorFlow, or PyTorch. Experience with SQL, NoSQL, and big data technologies (Spark, Hadoop, Snowflake, Databricks, etc.). Strong background in statistical modelling, probability theory, and mathematical optimization. Experience More ❯

experimental design. Experience with predictive modeling techniques such as regression, classification, clustering, or time-series forecasting. Proficiency in Python and experience with data science libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost, PyTorch, TensorFlow). Strong experience with SQL and data manipulation across large datasets. Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Plotly, Tableau, or Power BI). More ❯

TensorFlow and PyTorch. Programming: Solid experience in Python and SQL. Experience with R is a nice-to-have. ML and AI: Practical experience using ML modeling libraries like Scikit-Learn, Keras, Tensorflow, PyTorch and similar Generative AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on More ❯

tooling to get bootstrapped quickly is a must. Core AI & Machine Learning Python Vertex AI/Hugging Face LangChain/BAML — LLM frameworks Langfuse, LangSmith — Observability Pandas, NumPy, scikit-learn, PyTorch — Data & ML stack Data & Infrastructure BigQuery — Cloud data warehouse PostgreSQL — Application data Pulumi — Infrastructure as Code (TypeScript) Google Cloud Platform (GCP) — Cloud provider GitHub Actions — CI/ More ❯

at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

monitoring , and adoption of emerging AI tech. What We’re Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving skills. Passion for innovation and ethical More ❯

or technical field (Statistics, Mathematics, Physics, Computer Science, Machine Learning) Strong programming skills in Python (production-level) and SQL; confident with modern ML/AI libraries such as scikit-learn, TensorFlow, or PyTorch Familiarity with MLOps frameworks, model deployment, and cloud-based platforms (Databricks, AWS, Azure) Strong experience with data visualisation tools and techniques; able to turn complex More ❯

experience in data engineering, especially with advanced SQL and big data pipeline skills You'll have over 3 years of experience in machine learning with frameworks (such as Scikit-Learn, Keras, TensorFlow, PyTorch, Mllib) Excellent knowledge of analytical techniques, especially in the field of machine learning and pattern recognition and optimization Experience using Big Data platforms (Spark, Hadoop More ❯

CHEP helps move more goods to more people, in more places than any other organization on earth via our 347 million pallets, crates and containers. We employ approximately 13,000 people and operate in 60 countries. Through our pioneering and More ❯

CHEP helps move more goods to more people, in more places than any other organization on earth via our 347 million pallets, crates and containers. We employ approximately 13,000 people and operate in 60 countries. Through our pioneering and More ❯

solutions Key Skills & Experience Required Senior-level experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian More ❯

machine learning algorithms, optimization, architectures, and evaluation. Experience with data engineering workflows, including ETL, pipeline design, and feature extraction. Proficiency in Python and libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, and OpenAI/Anthropic APIs. Familiarity with DevOps & tooling (Git, CI/CD, API integration), front-end & visualization (Streamlit, Gradio, React), and cloud environments (AWS More ❯

3+ years of professional experience in data science or applied analytics. Are highly skilled in Python and Jupyter notebooks. Have experience using libraries including numpy, pandas, scipy, sympy, scikit-learn, torch, tensorflow. Have a bachelor's degree in data science, statistics, computer science, or related field in the U.S., Canada, New Zealand, UK or Australia. Have a strong More ❯

experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and large language models (LLMs), encompassing deployment, monitoring, and retraining. Familiarity with software engineering guidelines: version control (e.g., Git), CI More ❯

managing computational resources, and ensuring reliability and maintainability. Programming & ML/LLM Frameworks Strong expertise in Python and relevant ML/LLM libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn). Strong in Python, API design, asynchronous programming, and integration patterns. Hands-on with LangGraph/LangChain, LlamaIndex or Semantic Kernel for orchestration (tools, agents, guards, structured I More ❯

large data sets, modelling and evaluation Good understanding of software engineering concepts, particularly with machine learning development Experience with machine learning Python frameworks such as PyTorch, Tensorflow and Scikit-Learn For more senior candidates: Understanding of, including published work within, related academic fields such as NLP, Computer Vision or Deep Learning Relevant industry experience with demonstrable impact in More ❯

hands-on experience with Databricks, Python, PySpark, and SQL. Machine learning experience in a cloud environment (AWS, Azure, or GCP). Strong understanding of ML libraries such as scikit-learn, TensorFlow, or MLflow. Solid background in data modelling, ELT/ETL processes, and analytics best practices. If youre ready to make an impact in a growing tech company More ❯

hands-on experience with Databricks, Python, PySpark, and SQL. • Machine learning experience in a cloud environment (AWS, Azure, or GCP). • Strong understanding of ML libraries such as scikit-learn, TensorFlow, or MLflow. • Solid background in data modelling, ELT/ETL processes, and analytics best practices. If you’re ready to make an impact in a growing tech More ❯

partners, translating complex ML concepts for stakeholders. Who we're looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. You possess strong Python skills and solid experience in software engineering best practices. You bring hands-on experience with cloud platforms and infrastructure (e.g., AWS More ❯

going deep on particular topics and demonstrating breadth of knowledge to solve almost any problem. You possess strong Python skills and practical experience operationalising models using frameworks like Scikit-learn, TensorFlow, or PyTorch. You are an expert in at least one major Cloud Solution Provider (e.g., Azure, GCP, AWS) and have led teams to build full-stack web More ❯

experience with version control tools, preferably Git. Proficiency in Docker and container orchestration. Advanced proficiency in Python and familiarity with AI and machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of algorithms, data structures, and software engineering principles. Experience in deploying AI models in a production environment. Proven ability to collaborate effectively with cross-functional More ❯

aid the Principal Data Scientist to develop long term roadmaps and be comfortable presenting to Data leaders when needed. Strong working knowledge of modern ML frameworks (e.g., XGBoost, Scikit-learn, TensorFlow) and experience applying them to real-world problems. Proficiency in writing clean, maintainable, and efficient code in Python and SQL. Solid understanding of software engineering principles, including More ❯

What We're Looking For A Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or a related field. Strong experience with Python and data science libraries (Pandas, Scikit-learn, etc.). Solid understanding of machine learning concepts and algorithms . Interest in working with real-world industrial or sensor data . Exposure to Apache Airflow and/ More ❯

publications and preprints. Strong breadth and expertise in Statistical analysis, machine learning, data visualization, programming (Python, R, etc.), data cleaning and data manipulation. Tools: Python, R, SQL, TensorFlow, Scikit-learn, Tableau, Power BI. Ability to generate high quality ideas and be self-driven to explore. Strong experience in programming and comfortable modifying existing code-base. Experience with Python More ❯

and explore practical applications of AI. Overview of AI and Machine Learning Types of machine learning (supervised, unsupervised, reinforcement) Introduction to Python Libraries for AI - NumPy, Pandas, Matplotlib Scikit-learn for machine learning Building AI Models Data preprocessing Training and evaluating models Advanced Programming for AI Integration This programme aims to equip participants with the knowledge and practical More ❯