1 to 25 of 70 Permanent scikit-learn Jobs in the UK

across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js ...

across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js ...

able to hold or gain a UK government security clearance. Preferred Technical And Professional Experience Familiarity with machine learning frameworks (TensorFlow, PyTorch, scikit-learn). Experience with cloud platforms (AWS, Azure, Google Cloud). Knowledge of big data technologies (Hadoop, Spark). Background in supply chain management, pricing ...

million users without incurring technical debt. Strong programming skills in Python and familiarity with ML libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar. MLOPS experience with tools such as Drift, Decay, A/B Testing. Integration and Differential testing, python package building, code version etc. ...

into clear business value and influencing enterprise AI strategy. Knowledge, Qualifications and Experience Expertise in Python and key data science libraries (NumPy, Pandas, Scikit-Learn, PyTorch, TensorFlow) with strong ML/AI knowledge, including deep learning, time-series modelling, and LLMs (fine-tuning, RAG). Hands-on experience ...

looking for someone with a strong technical foundation, an innovative mindset, and a collaborative spirit. Technical skills (essential): Expertise in Python (NumPy, pandas, scikit-learn) and SQL Experience with EDA, data wrangling, and visualization tools (e.g., Matplotlib, Plotly, BI tools) Ability to build, evaluate, and deploy ML models ...

statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have ...

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 ...

Cortex) Understanding of natural language processing, computer vision, and recommender systems Strong programming skills in Python, SQL and proficiency with ML libraries (e.g. scikit-learn, pandas, NumPy, XGBoost, LightGBM) Soft Skills Strong analytical and problem-solving mindset with attention to detail Ability to work independently and drive projects ...

Cortex) Understanding of natural language processing, computer vision, and recommender systems Strong programming skills in Python, SQL and proficiency with ML libraries (e.g. scikit-learn, pandas, NumPy, XGBoost, LightGBM) Soft Skills Strong analytical and problem-solving mindset with attention to detail Ability to work independently and drive projects ...

Cortex) Understanding of natural language processing, computer vision, and recommender systems Strong programming skills in Python, SQL and proficiency with ML libraries (e.g. scikit-learn, pandas, NumPy, XGBoost, LightGBM) Soft Skills Strong analytical and problem-solving mindset with attention to detail Ability to work independently and drive projects ...

natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ? Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) ? Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks. ? Experience with ML Ops, including model deployment, monitoring ...

complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple ...

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 ...

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 ...

data roles (i.e., data engineer/scientist/software developer) in a professional environment Deep expertise in Python (pandas/polars, NumPy, scikit-learn a plus) and strong SQL; hands-on experience with dbt and Snowflake preferred Fluency with GitHub and DevOps/infra concepts (CI/ ...

supervised/unsupervised learning, deep learning, NLP, computer vision, and generative AI Familiarity with modern AI/ML frameworks and tools (TensorFlow, PyTorch, scikit-learn, etc.) Understanding of cloud platforms (AWS, Azure, GCP) and MLOps practices Knowledge of data engineering, APIs, and software development lifecycle Strong business acumen ...

DevOps practices (Infrastructure-as-Code). Proficiency with Git, Unix/Linux, Docker. Familiarity with ML frameworks such as TensorFlow, PyTorch, Keras, or scikit-learn (commercial experience not essential). Excellent communication skills for both internal and client-facing interactions. Awareness of MLOps is a plus. UK citizenship ...

DevOps practices (Infrastructure-as-Code). Proficiency with Git, Unix/Linux, Docker. Familiarity with ML frameworks such as TensorFlow, PyTorch, Keras, or scikit-learn (commercial experience not essential). Excellent communication skills for both internal and client-facing interactions. Awareness of MLOps is a plus. UK citizenship ...

statistical modelling, and modern AI techniques (supervised/unsupervised, time-series, Bayesian, deep learning). 🐍 Strong Python engineering skills — NumPy, Pandas, Scikit-Learn, plus PyTorch/TensorFlow. 🏗 Experience building scalable ML systems in production (ML Ops, CI/CD for ML, model optimisation). 🚀 Proven experience ...

Hands-on experience training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (e.g. scikit-learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity ...

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. Actively contributes to open-source AI projects, research ...

Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven ...

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 ...

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 ...