23 of 23 Permanent scikit-learn Jobs in Central London

stack products Strong backend (Node.js, Python/Flask, FastAPI) and frontend (React, Next.js, Vue) fundamentals ML/data science proficiency: Python, SQL, pandas, scikit-learn, PyTorch/TensorFlow Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Proven ability to build data-secure, privacy-compliant infrastructure ...

experimentation, model training/deployment, RAG pipeline development, prompt engineering) and tools/languages such as Python, Spark, notebooks, and ML frameworks (e.g., scikit-learn, MLflow, TensorFlow/PyTorch, LangChain, LlamaIndex at a conceptual level). Consulting Skills Skilled at asking the right questions to uncover technical requirements ...

experimentation, model training/deployment, RAG pipeline development, prompt engineering) and tools/languages such as Python, Spark, notebooks, and ML frameworks (e.g., scikit-learn, MLflow, TensorFlow/PyTorch, LangChain, LlamaIndex at a conceptual level). Consulting Skills · Skilled at asking the right questions to uncover technical requirements ...

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 ...

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 ...

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 ...

full-cycle AI software and deploying production-ready solutions. Strong proficiency in Python and core AI/data science libraries, such as: PyTorch, TensorFlow, ScikitLearn, Keras, NumPy, Pandas PyTorch Geometric, JAX, XGBoost, OpenCV Transformers, LangChain, Pinecone Hands-on experience with cloud computing systems for training, optimising, and deploying models. Strong ...

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 ...

engineering, AI engineering, or applied data science. Proven track record deploying AI/ML solutions into production. Expertise with ML frameworks (scikit‐learn, XGBoost, PyTorch, TensorFlow, LightGBM). Solid experience with LLMs, prompt engineering, RAG, and evaluation. Strong software engineering and MLOps skills (CI/CD, containers, monitoring ...

privacy standards, particularly in the handling of sensitive client data. The Candidate Advanced Python skills - Essential, with strong knowledge of Pandas, Numpy, and Scikit-learn Degree in computer science, data science, maths, engineering or similar Strong understanding of machine learning models and model appropriateness, probability and statistics Strong ...

Machine Learning Strong experience in Computer Vision (e.g. object detection, image classification, segmentation) Experience building, training and optimising ML models Python (NumPy, Pandas, scikit-learn) and frameworks such as TensorFlow or PyTorch Experience deploying models into production environments (cloud platforms, Docker, CI/CD pipelines) Clearance requirements: Active ...

actionable insights What We’re Looking For 🚀 Graduates up to 3 years’ experience in data science or analytics 🐍 Strong Python skills (pandas, numpy, scikit-learn) 🗄️ Solid SQL for data extraction and manipulation 📊 Experience with Tableau or Power BI is a bonus 🧠 Strong problem-solving and analytical thinking 🎤 Clear ...

deploying data science workflows at scale Strong grasp of statistical methods and core machine learning algorithms , with practical experience using libraries such as scikit-learn, statsmodels, and the ability to select appropriate models based on data characteristics and problem context. Why Synthesis? Synthesis is known for delivering exceptional ...

academic background (Bachelor’s degree 2:1 or above in a quantitative subject). Strong Python skills and experience with ML frameworks (e.g. scikit-learn, TensorFlow, PyTorch). Experience with model deployment, monitoring and ML pipelines (e.g. CI/CD, MLOps concepts). A collaborative mindset with strong ...

commercial impact. A strong academic background (Bachelor’s degree 2:1 or above in a quantitative subject). Strong Python skills (Pandas, NumPy, Scikit-learn or similar). A collaborative mindset with excellent communication skills. Experience working in cross-functional teams delivering production-ready solutions. If this role ...

commercial setting. Proven track record in customer or marketing analytics - understanding acquisition, engagement, churn, and lifetime value. Proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels) for data wrangling, analysis, and modelling. Ability to communicate complex findings in a clear, business-relevant way. Experience working collaboratively in agile, cross ...

Python (for ML development) and JavaScript/TypeScript (for production integration). Deep understanding of ML/DL frameworks such as PyTorch and scikit-learn . Hands-on experience with state-of-the-art foundation models, embeddings, and RAG. Strong knowledge of cloud computing, microservices, API design ...

experience working on classification or categorisation problems (ideally transaction, text, or behavioural categorisation). Strong proficiency in Python and ML libraries (e.g., XGBoost, scikit-learn, pandas). Comfortable working with SQL and large datasets (BigQuery experience a strong plus). Experience evaluating model performance rigorously and iterating based ...

Data/Machine Learning Ops Engineer Location: Erskine, Scotland (Hybrid 2/3 days per week in the office) Candidates must be eligible for clearance. DXC Technology (NYSE: DXC) is a leading independent, end-to ...

This is a unique opportunity to work at the cutting edge of AI, data technology, and elite football analytics. As a Data Scientist, you’ll join a collaborative, high-performing team with a culture rooted ...

Senior Data Scientist Hybrid - 1/2 days a week in Guildford Up to £80,000 About the Role Our client is a specialist technology and analytics consultancy delivering advanced data science solutions into complex ...

Senior Machine Learning/AI Engineer £100,000-£125,000 Hybrid working model: three days per week in the office (Monday, Tuesday, plus one flexible day) LDN 27 days of annual leave plus 8 bank ...