5 of 5 XGBoost Jobs in Central London

data-driven solutions. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong Python skills (bonus: C++, SQL, Spark) Experience in ML algorithms (XGBoost, clustering, regression) Expertise in Time Series, NLP, Computer Vision, MLOps Knowledge of AWS/Azure/GCP, CI/CD, and Agile development Ability to own solutions and manage stakeholders More ❯

learning Proven experience working with consumer behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data More ❯

For: 2–4 years of experience in data science, machine learning, or commercial/pricing analytics. Proficiency in Python/R, SQL , and ML libraries (e.g., scikit-learn, TensorFlow, XGBoost). Experience with data visualisation tools (Tableau, Power BI) and statistical methods. Ability to communicate insights clearly to non-technical stakeholders. Passion for applying AI/ML to solve complex More ❯

Data Scientist include: 2–5 years’ experience in data science or analytics, with strong Python and SQL skills Practical knowledge of machine learning techniques and tools (e.g., scikit-learn, XGBoost) Experience working with real-world datasets and presenting insights to stakeholders Excellent communication skills and the ability to explain complex ideas clearly 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 ❯