1 to 25 of 199 scikit-learn Jobs in England

production-grade analytical solutions. Hands-on experience with cloud platforms (Azure, AWS and/or Snowflake). Expertise in modern machine learning frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow). Demonstrable experience delivering end-to-end ML and GenAI solutions (including RAG, LLMs, embeddings and vector databases). Strong ...

Skills (What we're looking for) Technical Skills: · Strong programming skills in Python with expertise in ML/Al libraries (e.g., TensorFlow, PyTorch, scikit-learn, Keras). · Experience working with large datasets and using tools such as Pandas, NumPy, and Matplotlib. · Proficiency with cloud platforms like AWS, Azure ...

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. ...

learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science or machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Solid understanding of software engineering principles, including object-oriented programming, data structures, algorithms, and design patterns. Ability to quickly ...

Computer Science, Data Science, Statistics, Mathematics, or a related field . Strong proficiency in Python and key data science libraries ( NumPy, pandas, scikit-learn, Matplotlib, Seaborn ). Basic understanding of supervised and unsupervised learning algorithms (e.g., regression, classification, clustering). Knowledge of data querying and manipulation using ...

exposure to ML lifecycle. Hands-on experience building or maintaining ML workflows or pipelines. Strong Python skills and experience with tools like MLflow, Scikit-learn, or PyTorch. Familiarity with cloud platforms (especially Azure, AWS). Good understanding of containerisation (Docker) and orchestration (e.g. Kubernetes). Exposure ...

prioritisation What We're Looking For Strong operational research and optimisation background - this is a must Fluent Python, with hands-on experience of scikit-learn, pandas, numpy, Gurobi or similar OR packages Production ML/optimisation software experience - you've shipped models that run at scale Cloud platform ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/ ...

learning technologies and best practices Skills and Experience • Strong programming skills in Python • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment ...

degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline. Strong proficiency in Python or R, including libraries such as pandas, scikit-learn, NumPy, TensorFlow, or PyTorch. Solid understanding of statistical analysis, hypothesis testing, and experimental design. Hands-on experience applying a range of supervised ...

automation of analytical workflows. Collaborate with traders, quants, and technologists to identify data-driven opportunities. Profile Strong programming skills in Python (pandas, NumPy, scikit-learn) and SQL. Experience in data science , machine learning, and predictive modelling. Background in data engineering (ETL pipelines, streaming tech like Kafka). Familiarity ...

closely related field Strong foundations in machine learning, algorithms, and statistics Experience with Python and common ML libraries (e.g. TensorFlow, PyTorch, scikit-learn) Understanding of software engineering fundamentals and version control (e.g. Git) Ability to communicate technical ideas clearly to both technical and non-technical stakeholders Right ...

enterprise environments Deep understanding of algorithm selection, model complexity trade-offs, and overfitting/underfitting dynamics Strong proficiency in Python and ML ecosystems (scikit-learn, pandas, NumPy) Experience with deep learning frameworks (PyTorch or TensorFlow) Practical knowledge of deep learning architectures (CNNs, RNNs, Transformers) and when to apply ...

experience delivering end-to-end ML or AI solutions into production environments* Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn* Experience working with LLMs, including prompt design, RAG, or fine-tuning* Experience building APIs and integrating AI systems into real products* Solid understanding ...

Python and its core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra ...

conversational AI, recommendation systems, optimisation, or marketing analytics. Deep understanding of ML fundamentals across the full lifecycle. Hands‐on experience with ML frameworks (scikit‐learn, XGBoost, PyTorch, TensorFlow, LightGBM). Strong exposure to LLMs, prompt engineering, RAG, and evaluation frameworks. Familiarity with MLOps tooling: CI/CD, experiment ...

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 ...

enterprise environments Deep understanding of algorithm selection, model complexity trade-offs, and overfitting/underfitting dynamics Strong proficiency in Python and ML ecosystems (scikit-learn, pandas, NumPy) Experience with deep learning frameworks (PyTorch or TensorFlow) Practical knowledge of deep learning architectures (CNNs, RNNs, Transformers) and when to apply ...

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, gurobi etc.) to solve real-life problems and visualise the outcomes (eg seaborn) Proficient in working with cloud platforms (AWS preferred ...

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/ ...

client in conjunction with this vacancy only. KEY SKILLS AI, Python, Machine Learning, Software Engineering, Data, APIs, Cloud, Agile, Python, TensorFlow, PyTorch, Scikit-learn, XGBoost, NLTK, OpenAI, LangChain, Pandas, NumPy, MLflow, Kubeflow, Docker, Kubernetes, Azure Machine Learning, Google Vertex ...

inference techniques (e.g., diff-in-diff, IV, matching) where randomisation is impractical Fluency in Python and core data/ML libraries (pandas, NumPy, scikit-learn, PyTorch or TensorFlow), combined with solid software engineering practices (clean code, testing, version control, code review) Proficient with large-scale data : strong ...

applications from women who are passionate about machine learning and eager to grow: Strong Python skills and experience with ML libraries (pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, Keras, PyTorch). Familiarity with model deployment and serving tools (ONNX, TensorRT, TensorFlow Serving, TorchServe). Experience with ...