16 of 16 XGBoost Jobs in London

feature engineering, validation, model evaluation and optimisation. · Hands-on experience with Python-based machine learning libraries, especially Scikit-Learn and at least one of XGBoost, LightGBM, TensorFlow or PyTorch. · Experience developing models beyond exploratory analysis into reusable, documented and testable assets, ideally with exposure to pilot or production environments. · Strong ...

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 ...

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 ...

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 ...

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 ...

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 ...

clustering, ranking, NLP, or LLMs).Data & ML Ecosystem: Familiarity with data processing libraries (e.g. Pandas, NumPy) and ML frameworks (e.g. PyTorch, Scikit-learn or XGBoost).Growth Mindset: A genuine interest in distributed system and software design, concurrent algorithms, data structures, and software engineering. At Quantcast, we craft offers that reflect ...

learning models across the full lifecycle Develop and enhance Probability of Default (PD) models and scorecards Create revenue forecasting models using techniques such as XGBoost and CatBoost Partner with business stakeholders to solve complex commercial problems Support the evolution of data science infrastructure and best practices Your Skills & Experience Strong ...

Skills, Knowledge and ExpertiseHands-on training and evaluation of tabular models, using neural networks or gradient-boosted trees. Experience with PyTorch, PyTorch Lightning, TensorFlow, XGBoost, CatBoost or scikit-learn could all be relevant; no single framework is required. Experience designing features and labels, choosing metrics for the decision a model ...

production Essential skills & experience Classical/traditional ML: Proven experience with models such as linear and logistic regression, decision trees, random forests, gradient boosting (XGBoost, LightGBM), SVMs and clustering. You can explain which models you've used, why you chose them and what alternatives you considered. Python: Strong proficiency ...

instinct for leakage, bias and overfitting in messy real-world data. Strong ML fundamentals across classical ML and deep learning (pandas, scikit-learn, XGBoost or LightGBM, PyTorch), and the judgement to tell when a language model is the wrong tool. A deep understanding of how modern models are built ...

maintain machine learning solutions in production. Experience with learning-to-rank methodologies is highly desirable. Exposure to tools and techniques such as Metaflow, XGBoost, PyMC, Streamlit, propensity modelling, or optimisation methods would be beneficial. Experience within digital marketplaces, travel platforms, e-commerce, classifieds, or consumer-facing search environments is advantageous. ...

operational excellence. Experience working with large-scale data processing technologies such as Spark. Strong understanding of machine learning frameworks such as PyTorch, TensorFlow, XGBoost or similar technologies. Experience designing reliable APIs, services and platforms that support machine-learning-powered products. Ability to work through ambiguity and lead complex technical initiatives. ...

measuring ranking or recommendation changes against commercial KPIs Strong hands-on Data Science background Nice to have: Learning-to-rank/re-ranking Metaflow XGBoost/LightGBM Propensity modelling Optimisation PyMC Streamlit Cold-start recommendation Travel, ecommerce, marketplace or booking-platform experience Contract: 3-4 months Rate: £480/ ...

understanding of computer science fundamentals and time-series forecasting Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning) Machine Learning Engineer, XGBoost, GCP, Python, SQL, time-series forecasting Reasonable Adjustments: Respect and equality are core values to us. ...