21 of 21 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 ...

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, semanticsearchand knowledge graphs. Actively contributes to open-source AI projects, researchpublicationsand industry events/websites. Familiarity ...

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 ...

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 ...

expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit‐learn, PyTorch, XGBoost) and cloud‐native ML services (SageMaker, Azure ML, Vertex AI). Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure ...

lifecycleexpertise: feature engineering, model training,evaluationand production deployment, includingMLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn,PyTorch,XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Platform & Cloud Engineering Architecture and delivery of scalable cloud data and AI platforms on AWS,Azureor ...

machine learning services using one or more cloud providers (preferably GCP). Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.). Strong knowledge of SQL and Python’s ecosystem for data analysis (Jupyter, Pandas, Scikit ...

based machine learning services using one or more cloud providers (preferably GCP) Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn ...

dynamic, iterative environment No industry knowledge required Technical skillset - Must: Python common data science/ML libraries (e.g., pandas, NumPy, scikit-learn, XGBoost, PyTorch, Hugging Face) experiment design evaluation metrics Nice to have: LLM fine-tuning prompt engineering SQL/PostgreSQL #J-18808-Ljbffr ...

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). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community ...

engineers who have experience in many of the following areas: Strong Python development experience Machine Learning frameworks such as PyTorch, TensorFlow, Scikit-learn or XGBoost AWS services including SageMaker, Lambda and S3 MLOps tooling such as MLflow, Weights & Biases or DVC Experiment design, testing and statistical evaluation Generative AI, LLMs ...

team. What We're Looking For Strong commercial experience developing machine learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data ...

related quantitative field. Expert proficiency in GCP’s ML/AI tooling, its data ecosystem, and Python with core ML/AI libraries (PyTorch, XGBoost, TensorFlow). Expert proficiency with SQL development, with Google dialects being advantageous. Proficiency with an API web framework (FastAPI, Django, Flask). Robust CI/ ...

learning and predictive modelling projects Advanced Python and SQL skills Experience working with large and complex datasets Knowledge of machine learning techniques such as XGBoost, CatBoost, or related models Experience working in cloud-based environments, ideally Azure Strong stakeholder management and communication skills Ability to translate business challenges into analytical ...

Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression‐based approaches. Assist in designing and implementing end‐to‐end data ingestion processes, ensuring seamless data flow to investing teams. ...

operating models on Databricks. Familiarity with cloud‐based application development (AWS & Azure). Familiarity with one or more ML frameworks and technologies: scikit‐learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, Triton. Strong communication skills, able to express ideas clearly and collaborate across teams. #J-18808-Ljbffr ...

refine problem statements and propose solutions considering effort, impact, and scalability trade-offs; Nice to have: Apache Spark, Iceberg, Kafka, dbt, Scikit-Learn, XGBoost, PyTorch, MLFlow, GraphFrames, Ray, AWS S3, EMR, SageMaker, Lakeformation, Terraform, Docker, GitHub CI/CD, Knowledge Graphs, RAG, graph ML, probabilistic programming, A/B testing. ...

operating models on DatabricksFamiliarity in Cloud-based application development (we use AWS & Azure)Familiarity with one or more ML frameworks and technologies: scikit-learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, TritonStrong communication skills, able to express ideas clearly and collaborate across teamsAdditional InformationBring ...

projects Requirements: Recent graduates or final year students. Should desirably have knowledge of Artificial Intelligence modeling techniques (logit, GLM, time series, random forests, clustering, XGBoost), statistical programming languages (SAS, R, Python, Matlab), big data tools and platforms (Hadoop, Hive, etc.) and cloud platforms (AWS, Azure, GCP). Solid academic record. ...

Deep expertise with AWS SageMaker (training, processing, pipelines, endpoints, registry) and complementary AWS services. Expert‐level Python and ML Model frameworks (e.g. PyTorch, TensorFlow, XGBoost). Strong thought leadership in MLOps automation, CI/CD for ML, and model lifecycle management. Advanced experience designing explainability systems, reason codes, and governance ...

identify gaps between predicted vs. actual claim costs Working with large, messy insurance datasets across multiple product lines Tools & tech: Python, SQL, AzureML, XGBoost Opportunity to mentor within the team #J-18808-Ljbffr ...