23 of 23 XGBoost Jobs in England

6+ years of experience in ML Engineering or Data Science (finance, fintech, or treasury a plus). Proficiency in Python-including pandas, scikit learn, TensorFlow/PyTorch, LightGBM/XGBoost-and experience with SQL. Hands on experience with cloud ML platforms (AWS SageMaker, Azure ML, or Google AI Platform). Solid understanding of software engineering fundamentals: version control, code reviews More ❯

experience with software testing (unit, integration, system), and knowledge of test-driven development; other languages are a plus. Proficiency in at least one ML framework, such as scikit-learn, XGBoost, Tensorflow, or PyTorch. Proficiency with Cloud platform(s), such as Google Cloud Platform, Amazon Web Services, or Azure. Experience in designing, and deploying ML pipelines in production environments; knowledge of More ❯

Python, including solid experience with software testing (unit, integration, system), and knowledge of test-driven development; other languages are a plus. Proficiency in ML frameworks, such as scikit-learn, XGBoost, Tensorflow, or PyTorch. Proficiency with Cloud platform(s), such as Google Cloud Platform, Amazon Web Services, or Azure. Experience in designing, and deploying ML pipelines in production environments; knowledge of More ❯

What we offer Solid understanding of computer science fundamentals, data structures, algorithms, data modelling and software architecture Solid understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.), state-of-the-art areas (e.g. NLP, Transfer Learning) and modern Deep Learning algorithms (e.g. BERT, LSTM) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter More ❯

Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written and verbal communication More ❯

Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written and verbal communication More ❯

Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written and verbal communication More ❯

Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written and verbal communication More ❯

Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written and verbal communication More ❯

key machine learning models, including Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile - you should be happy working More ❯

solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI/CD More ❯

even better. You’ll need a Master’s or PhD in a quantitative field, strong Python skills, and extensive experience applying core machine learning libraries such as Scikit-learn, XGBoost, or LightGBM to structured data problems. The role may also involve developing and deploying deep learning models using frameworks like PyTorch or TensorFlow where appropriate. Experience with version control (Git More ❯

latent class, hierarchical, and factor analysis. Understanding of working with market research and customer databases. Knowledge of statistics and machine learning applications. Experience with predictive modeling using linear models, XGBoost, discriminant analysis, etc. Beneficial Skills Experience with conjoint analysis and other pricing methods. Knowledge of GDPR and data compliance. Experience working with third-party data vendors and APIs. Some familiarity More ❯

services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Machine Learning Engineer, timeseries, forecasting, VertexAI More ❯

high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn, XGBoost, or LightGBM Strong SQL skills for data extraction and transformation Experience working with transactional (e.g., Open Banking) and bureau data (e.g., Experian, Equifax) Expertise in feature engineering, handling class imbalance More ❯

high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn, XGBoost, or LightGBM Strong SQL skills for data extraction and transformation Experience working with transactional (e.g., Open Banking) and bureau data (e.g., Experian, Equifax) Expertise in feature engineering, handling class imbalance More ❯

skills for AI/ML applications - clean, well-tested code, version control best practice, and smooth integration with back-end systems. Hands-on experience with gradient-boosted models (e.g., XGBoost, LightGBM) and/or building LLM-powered systems (e.g. tool/function calling, prompt design, evals) for text-heavy tasks. Solid data skills: SQL, pandas, experiment tracking, and cloud deployment More ❯

implementing machine learning models, and bridging the gap between data science and data engineering where necessary. As a Data Scientist, you will be experienced with: ML techniques - linear regression, XGBoost, ensemble methods Python ETL pipelines AWS, Azure, or GCP SHAP or LIME tool familiarity Key information: Up to £450 per day Outside IR35 6 months (rolling) Hybrid Weekly - Manchester This More ❯

implementing machine learning models, and bridging the gap between data science and data engineering where necessary. As a Data Scientist, you will be experienced with: ML techniques - linear regression, XGBoost, ensemble methods Python ETL pipelines AWS, Azure, or GCP SHAP or LIME tool familiarity Key information: Up to £450 per day Outside IR35 6 months (rolling) Hybrid Weekly - Manchester This More ❯

implementing machine learning models, and bridging the gap between data science and data engineering where necessary. As a Data Scientist, you will be experienced with: ML techniques - linear regression, XGBoost, ensemble methods Python ETL pipelines AWS, Azure, or GCP SHAP or LIME tool familiarity Key information: Up to £450 per day Outside IR35 6 months (rolling) Hybrid Weekly - Manchester This More ❯

Job Title: Data Scientist (LLMs & ML) - UK Remote A fast-growing healthcare organization is seeking a Data Scientist with strong experience in machine learning, deep learning, and Large Language Models (LLMs) to help drive innovation and automation in clinical services. More ❯

Job Title: Data Scientist (LLMs & ML) - UK Remote A fast-growing healthcare organization is seeking a Data Scientist with strong experience in machine learning, deep learning, and Large Language Models (LLMs) to help drive innovation and automation in clinical services. More ❯

Job Title: Data Scientist (LLMs & ML) - UK Remote A fast-growing healthcare organization is seeking a Data Scientist with strong experience in machine learning, deep learning, and Large Language Models (LLMs) to help drive innovation and automation in clinical services. More ❯