1 to 25 of 37 XGBoost Jobs in London

learning or statistical models within a commercial environment.Advanced proficiency in Python (pandas, NumPy, scikit-learn) and advanced SQL.Solid understanding of core ML algorithms (e.g. XGBoost, LightGBM, linear/logistic regression, clustering, time-series forecasting).Practical familiarity with software engineering best practice, including Git, code reviews and reproducible workflows.Awareness of modern ...

Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working in cloud-based environments (AWS or GCP) and familiarity with CI/ ...

Anaplan Applications, translating raw customer data into automated, high-value business insights. Advanced Modeling & Timeseries Forecasting: Design, train, and implement robust Machine Learning (LightGBM, XGBoost) and Deep Learning (PyTorch) models specifically focused on complex demand sensing and resolving cold-start forecasting problems. Feature Engineering Pipelines: Build and optimize scalable data ...

Engineering: Python proficiency, modular API design, creating reusable libraries, advanced SQL, and scalable data integration using ML/AI frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face).AI Architecture & Security: Proven ability to architect secure enterprise cloud environments, ensuring stringent adherence to identity and access management (IAM) protocols, data governance ...

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 publications. 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. Contributions to open-source AI projects or research publications. Familiarity with ...

strategic AI solutions. Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers). Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling, RAG, agents, prompt engineering ...

churn/retention propensity, Customer Lifetime Value, pricing optimisation, demand forecasting, lead scoring or recommendation systems. Strong Python for machine learning (scikit-learn, XGBoost/LightGBM, pandas and statistical libraries), with clean, tested and version-controlled code. Advanced SQL and experience with large-scale cloud data platforms such as Databricks ...

with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time series forecasting. Working understanding of model evaluation and explainability concepts, e.g. overfitting, bias, cross-validation. Experience developing and implementing ...

skills and experience working with large-scale relational and cloud-based databases (e.g., Snowflake,BigQuery). Experience with machine learning frameworks (e.g., scikit-learn,XGBoost, TensorFlow,PyTorch). Ability to work autonomouslyand comfortable with ambiguity. Experience in the healthcare field, preferably in generic pharmaceuticals (pricing,sourcingor distribution) preferred, though notrequired. ...

Machine Learning systems from research all the way to deployment and maintenance Excellent Python programming skills and hands on experience with libraries such as XGBoost, PyTorch, TensorFlow, or Hugging Face Experience working with cloud‐based data and AI platforms, particularly Azure and Databricks Strong stakeholder engagement and storytelling capabilities; able ...

time data is a strong plus Also desirable: experience with vector databases (pgvector, Pinecone, Weaviate, Qdrant or similar); machine learning experience (PyTorch, TensorFlow, XGBoost/LightGBM) for building, maintaining and extending existing models; Bloomberg API integration to Python; data science/statistics, signal research, backtesting or factor modelling; full stack ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing ...

cards, or BNPL. Deep proficiency in PD model development and validation, with strong knowledge of calibration techniques. Advanced Python and SQL skills; familiar with XGBoost, scikit-learn, pandas, MLFlow. Experience with explainability frameworks such as SHAP, LIME, PDP. Ability to communicate technical concepts clearly and influence cross-functional decisions. Familiarity ...

opportunities to improve business efficiency through intelligent automation. Skills & Experience Strong Python programming skills with experience using libraries such as Pandas, NumPy, Scikit-learn, XGBoost or LightGBM, and Plotly, Rust, Typescript, Python or Matplotlib. Experience developing machine learning models for prediction, optimisation or classification. Strong SQL skills and experience working ...

science, machine learning, pricing analytics, or commercial operations. Strong technical background in Python or R, SQL, and applied ML libraries (e.g. scikit-learn, TensorFlow, XGBoost). Experience with data visualization tools (Tableau, Power BI, or similar). Understanding of statistical methods, supervised/unsupervised learning, and business experimentation. Ability ...

also unstructured data eg. Text, PDFs, jpgs, call recordings, video,etc. Knowledge of machine learning modelling techniques and how to fine-tunethosemodels eg. XGBoost, Deep Neural Networks, Transformers, ResNets,VAEs, GANs,Markov chains, etc. Experience using specialized machine learning libraries eg. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. ...

SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM) Systemic Problem Solving: Ability to work on unique issues requiring conceptual thinking and broad impact. You know how to build for long-term ...

unstructured data eg. Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, ResNets, VAEs, GANs, Markov chains, etc. Experience using specialized machine learning libraries eg. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface ...

Airflow, Prefect, etc.). Hands-on experience with common ML libraries and frameworks, e.g. PyTorch, scikit-learn, and gradient-boosting libraries such as XGBoost or LightGBM. Clear evidence of practical experience defining and deploying containerised systems, i.e.: Implementing APIs for internal services, e.g. via FastAPI; Deploying containerised systems to production ...

platforms.Model Development, Governance & Explainability* Deep experience applying a wide range of machine learning techniques to real-world business problems, including using models such as XGBoost and deep learning approaches using frameworks such as PyTorch or TensorFlow, taking solutions from experimentation through to production deployment and operation.* Strong knowledge of model ...

kept working. Statistics and experimentation: hypothesis testing, A/B testing, power and sample sizing. Classical ML: classification and ranking with scikit-learn and XGBoost or LightGBM, evaluated rigorously: validation design, calibration, leakage. Decision science: applied work with at least one of contextual bandits, causal inference or uplift modelling ...

QlikSense Experience in SQL (any variant), Alteryx, MS Excel and VBA Experience in applying various analytical techniques (e.g. naïve bayes, decision trees, random forest, xgboost and k-means), to calculate problems such as predictive forecasting, prescriptive action, capacity planning. Experience of working in teams, managing the workload of junior team ...

Hands-on experience building credit scorecards or risk models (application, behavioural, or collections) Proficiency in Python and SQL; experience with ML frameworks (scikit-learn, XGBoost, etc.) Familiarity with Open Banking data, bureau data (Experian, Equifax, TransUnion), or alternative data sources Comfort working in small, fast-moving teams where you have ...