26 to 42 of 42 XGBoost Jobs in London

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 ...

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 ...

with enterprise‐level infrastructure and architecture, including a extensive understanding of APIs. You have experience building, tuning, or deploying ML models (e.g., scikit‐learn, XGBoost, PyTorch, TensorFlow) in production settings Experience with AI use cases in financial services (e.g. fraud detection, credit scoring, underwriting) is a strong plus. ...

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. ...

with: Data Quality Data Governance techniques Knowledge of: MLOps Feature Engineering Exposure to data analysis and ML tools such as: scikit-learn pandas NumPy XGBoost LightGBM Familiarity with orchestration tools: Apache Oozie Apache Airflow Why you’ll love it here We want to make Prima a happy and empowering place ...

team and stakeholders. Experience developing AI/ML algorithms and infrastructure. Excellent knowledge of Python, NumPy and Pandas. Experience with at least one of: XGBoost, LightGBM, CatBoost, TensorFlow, PyTorch, MOSEK, CVXPY. Graduate‐level research experience in Artificial Intelligence or related field, including work published or accepted to a major conference ...

drive measurable business value Strong expertise in Python and SQL Deep familiarity with pandas, NumPy, scikit-learn, and standard ML frameworks such as PyTorch, XGBoost, or LightGBM Experience working in cloud-based environments such as AWS or GCP Familiarity with CI/CD workflows, Git, and MLOps principles Ability … Mentoring Problem-Solving Adaptability Industry Keywords Data Products Business Insights Customer Behavior Modeling Forecasting Optimization Causal Inference Tools & Technologies Pandas NumPy Scikit-Learn PyTorch XGBoost LightGBM Git CI/CD Workflows MLOps Principles Cloud Platforms #J-18808-Ljbffr ...

exploring LLM-based feature engineering. You will collaborate with cross-functional teams, mentor juniors, and contribute to long-term modeling vision, leveraging Python, SQL, XGBoost, and MLFlow in a fast-paced environment. #J-18808-Ljbffr ...

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 ...

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. ...

trails Strong general insurance pricing toolkit: GLMs (Poisson/NB/Tweedie), GAMs, credibility/hierarchical methods; experience with tree-based ML (GBM/XGBoost/CatBoost) and regularisation Proficient in R and Python, with strong SQL; comfortable in Git-based workflows and “in the engine room” with proprietary rating ...

clear recommendations for engineering, product and commercial teams. You Need Expert Python and SQL, with experience building production ML systems and data pipelines (PyTorch, XGBoost, Spark/PySpark, Apache Iceberg, Ray, MLflow, SageMaker, Airflow, or equivalent). Deep experimentation and statistical inference skills, and a strong grasp of optimisation under ...

working software. Experience with any of the following would be an advantage: LLMs AI Agents Graph analytics Behavioural modelling Cyber security Network intelligence PyTorch XGBoost Our technology Python SQL AWS PyTorch Scikit-learn XGBoost Docker Kubernetes Claude Code GitHub Copilot LLMs AI Agents Why Friend MTS? AI is becoming ...

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. ...

Working with large datasets Production software development Experience with any of the following is useful, but not essential: LLMs AI Agents PyTorch XGBoost Graph analytics Behavioural modelling Cyber security Network analytics Our technology Our technology stack continues to evolve, but you'll typically work with: Python SQL AWS PyTorch Scikit … learn XGBoost Docker GitHub Claude Code GitHub Copilot LLMs AI Agents Why Friend MTS? You’ll work on problems very few engineers ever encounter. Internet-scale systems. Adversarial behaviour. Real-time intelligence. Applied AI. You’ll help build technology that protects some of the world's largest broadcasters, sports organisations ...

practices (with the freelance Lead Developer) that support Atlas's modelling, forecasting and MMM automation Support productionisation of propensity, forecasting and MMM outputs (e.g. XGBoost, AutoGluon/Chronos, Meridian) built by the Data Scientist, ensuring they run reliably at scale Implement data governance, monitoring, alerting and incident runbooks appropriate … with event streaming architectures (e.g. real‐time ingestion, sub‐second/sub‐minute latency pipelines) Exposure to productionising machine learning or forecasting models (e.g. XGBoost, AutoGluon, Meridian, Robyn) built by data scientists Experience with reverse ETL and activation into media, CRM or ESP platforms Hands‐on experience with Snowflake (warehouse ...