1 to 25 of 131 Permanent scikit-learn Jobs in the UK

technical processes. Required Skills & Qualifications Classic Machine learning (Regression, predictive Analysis, Classification, Clustering) Machine learning Model Optimisation Strong proficiency in Python (NumPy, Pandas, Scikit-learn). Hands-on experience with Deep Learning frameworks: TensorFlow, PyTorch, or Keras. Experience in Natural Language Processing (NLP) and/or Computer Vision. ...

language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries ...

automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation ...

setting. Education: Relevant Software Engineering/Computer Science degree. Technical Skills Programming Languages: Python, Java, C++, C#, TypeScript, JavaScript Machine Learning: TensorFlow, PyTorch, Scikit-learn GenAI/LLMs: OpenAI API, Hugging Face Transformers, LangChain, Langraph, RAG pipelines Data & Analytics: Pandas, NumPy, Spark, Databricks, Hadoop, Vector Databases, Snowflake Model ...

contribute to our internal library of proprietary tools and frameworks. Technical Profile Expert Programming: Mastery of Python and its ecosystem (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Experience writing production-ready, modular, and well-tested code. Advanced Modeling: Deep theoretical and practical knowledge of Machine Learning. ...

degree (Russell Group preferred) in Data Science, Computer Science, Mathematics, Physics, Engineering, or similar Excellent Python skills and ML foundations (e.g. pandas, NumPy, scikit-learn; strong coding practices matter) Strong grasp of model evaluation, statistics, and experimentation Confident working with data at scale using SQL (and a practical ...

GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

/Databricks Workflows Cloud Platforms Azure, AWS, or GCP (experience with at least one) Data Science & Optimisation Python ecosystem (Pandas, NumPy, SciPy, Statsmodels) Scikit‐learn, XGBoost, LightGBM, CatBoost Time‐series forecasting (Prophet, SARIMAX, ML‐based approaches) Optimisation frameworks (OR‐Tools, Pyomo) Agentic AI & LLMs (Nice to Have) LangChain ...

comply with strict risk, privacy, and ethical standards, including data governance and fairness in highly regulated financial settings. Key Technologies & Tools Core ML: scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM Data Manipulation: Pandas, NumPy, LangGraph MLOps & Orchestration: MLflow, Apache Airflow Databases: Neo4j, MongoDB API Development: FastAPI Big Data (Beneficial ...

technical stakeholders What we’re looking for Essential experience Strong grounding in statistical modelling, experimentation and inference Advanced Python skills (NumPy, pandas, scikit-learn, PyTorch or TensorFlow) Experience building, deploying and optimising ML models in production Strong AWS experience (e.g. SageMaker, Lambda or similar services) Expert SQL skills ...

engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI ...

Required Skills: Experience in data science, machine learning, or applied analytics Strong proficiency in Python and common ML libraries (pandas, NumPy, scikit‐learn, TensorFlow, PyTorch) Experience designing, training, and evaluating machine‐learning models Solid understanding of statistical methods, predictive modelling, and experimental design Experience working with large ...

data analysis or machine learning (internships, placements, academic or commercial projects) 🐍 Strong Python fundamentals and exposure to libraries such as pandas, NumPy, and scikit-learn 🧮 A solid understanding of statistics, data wrangling, and model evaluation 🗄 Confidence working with SQL and structured datasets ☁️ Familiarity with cloud platforms ...

into production environments. Key skills and experience include: Strong programming skills in Python Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn Advanced knowledge of statistics, probability, and optimisation techniques Proven experience building, testing, tuning, and optimising machine learning models Comfortable working with large, complex ...

mixed integer programming, heuristics) Fluent in Python(required) and other programming languages (preferred)with strong skills in applying DS, ML, and OR packages (scikit-learn, pandas, numpy, gurobietc.) to solve real-life problems and visualise the outcomes (e.g. seaborn) Proficient in working with cloud platforms (AWS preferred), code ...

Learning Engineer , ideally within Financial Services, FinTech, or a regulated environment Strong Python skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn) Experience deploying and supporting ML models in production Solid understanding of data pipelines, versioning, testing, and software engineering best practices Experience working with ...

Skilled at working with non-technical stakeholders to scope, design and deliver effective ML solutions. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research ...

research in machine learning, computational chemistry, and bioinformatics. Required Skills & Experience Proficiency in Python and the core data science ecosystem (e.g., Pandas, NumPy, Scikit-learn). Hands on experience with a modern deep learning framework, preferably PyTorch. Strong theoretical understanding of machine learning principles, including deep learning ...

systems, personalisation, or deep learning is desirable but not essential. Solid Python skills and experience with ML libraries such as pandas, numpy, scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps practices ...

Statistics, or related field Strong programming skills in Python (and optionally R, Java, or C++) Knowledge of ML frameworks like TensorFlow, PyTorch, or scikit-learn Eagerness to learn, curiosity, and a problem-solving mindset Nice to Have Cloud experience (AWS, GCP, Azure) Familiarity with MLOps tools (Docker ...

will not be considered) Experience with CI/CD pipelines for ML/DL models Proficiency in Python and common ML libraries (e.g. Scikit-learn, TensorFlow, PyTorch) Experience with container technologies (Docker, Kubernetes) Consultancy or client-facing experience preferred Strong communication and stakeholder management skills Qualifications IT/ ...

will not be considered) Experience with CI/CD pipelines for ML/DL models Proficiency in Python and common ML libraries (e.g. Scikit-learn, TensorFlow, PyTorch) Experience with container technologies (Docker, Kubernetes) Consultancy or client-facing experience preferred Strong communication and stakeholder management skills Qualifications IT/ ...

uphold best practices for deploying ML at scale Key skills & experience: • Strong Python and software engineering fundamentals • Experience operationalising ML models (e.g. Scikit-learn, TensorFlow, PyTorch) • Hands-on cloud experience (AWS, Azure or GCP), including security considerations • Containerisation and orchestration (Docker, Kubernetes) • Solid grounding in core ML concepts ...

solutions Implement experiment tracking and monitoring Collaborate with data scientists and engineers What We're Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps ...