10 of 10 Permanent XGBoost Jobs in London

solutions in industry or engineering environments. Strong expertise in Python and AI/ML libraries: PyTorch, TensorFlow, Scikit‐Learn, Keras, NumPy, Pandas, JAX, XGBoost, PyTorch Geometric, OpenCV, Transformers, LangChain, Pinecone . Proven hands‐on experience deploying models in production and building scalable AI software. Deep understanding of advanced modelling methods ...

data scientist (or similar role). Expert proficiency of Python and experience using SQL, alongside using common ML/AI packages (TensorFlow, PyTorch, XGBoost, etc.). Familiarity with statistical (e.g. GLM, GAMs) and deep learning techniques (e.g. neural networks, transformers, diffusion models, etc.). Comfortable designing and creating neural network ...

Computer Science, Mathematics, or similar Experience delivering predictive analytics or machine learning solutions Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda, Redshift) Ability to clearly communicate insights to non-technical stakeholders Strong analytical thinking, collaboration ...

regulatory and compliance implications in payments Experience working in payments transformation programs Technical Strong Python skills Experience with ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.) Experience with LLMs/GenAI frameworks (LangChain, RAG, prompt engineering, etc.) Experience in cloud (AWS/Azure/GCP) Experience in MLOps tools (MLflow ...

Machine Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version ...

commercial experience in machine learning or data science Strong Python skills with experience in ML frameworks such as scikit-learn, PyTorch, TensorFlow, or XGBoost Exposure to AWS services (e.g. S3, Lambda, SageMaker) Understanding of core ML concepts: model evaluation, validation, and experimentation Familiarity with MLOps or experiment tracking tools (e.g. ...

knowledge of Spark, SQL or other data-oriented programming language and are proficient with standard data wrangling and modelling libraries (e.g. Pandas, Sklearn, Keras, XGBoost, LightGBM) You're collaborative and pragmatic with great communication skills You're collaborative and pragmatic with great communication skills What ...

external business events is a strong plus. · Data & Traditional ML: Experience with Databricks for data engineering (PySpark) or building classical ML models (Scikit-Learn, XGBoost) is beneficial for handling complex data pre-processing and hybrid AI use cases. ...

SQL. Confident working with large, complex, or messy datasets. Experience applying machine learning techniques such as gradient-boosted models, with exposure to tools like XGBoost or CatBoost. Ability to form structured analytical approaches, make sensible assumptions, and communicate your reasoning clearly. Comfortable mentoring others and contributing to a cooperative team ...

modern AWS production environments. The Technical Reality: We operate a pragmatic stack where Linear Regression remains vital for stability and baseline performance, while XGBoost and LLMs are used as responsible additions. We are looking for someone who knows when to use a simple linear model and when to deploy … Responsibilities Predictive Modelling (Linear & Non-Linear): You will build and maintain foundational Linear Regression models for credit, affordability, and fraud scoring, while developing advanced XGBoost models for deeper risk insights. You will mine data to find behavioural signals—such as spending volatility or income stability—that predict affordability, repayment ...