26 to 50 of 59 XGBoost Jobs in the UK

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 ...

data 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 to interpret and communicate ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

report what the results do and don’t show Strong Python skills and hands‐on experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch or Keras Solid grounding in modern software engineering, infrastructure and data tooling, and an understanding of the MLOps challenges across the full ML lifecycle. ...

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. ...

libraries such as Pandas Strong understanding of Machine Learning, including both supervised and unsupervised techniques Experience with tree-based and boosting algorithms such as XGBoost, LightGBM, and related approaches Experience working with large-scale datasets, ideally using PySpark Strong analytical and SQL skills for handling, querying, and interpreting complex datasets ...

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 ...

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. ...

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 ...

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 ...

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 ...

Strong commercial Data Science experience Advanced Python and SQL skills Experience with Databricks and/or PySpark Knowledge of machine learning techniques such as XGBoost and LightGBM Strong statistical modelling capability Excellent problem-solving and stakeholder management skills Experience in insurance, financial services, or another regulated environment 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. ...

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 ...

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 ...

observability and operational excellence Experience 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 ...