26 to 50 of 50 XGBoost Jobs in England

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. ...

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 ...

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 ...

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 ...

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 ...

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 ...

ensemble techniques (e.g., Gradient Boosted Trees, Random Forests).Core Technical Proficiency: High proficiency in Python for data science (including libraries like Pandas, Scikit-Learn, XGBoost/LightGBM) and SQL.Large-Scale Data Expertise: Demonstrable experience working with very large, complex, and sometimes messy datasets to build effective models. Experience with geospatial ...

/Senior) to analyse longitudinal healthcare datasets and build predictive models. The role emphasizes Python/SQL proficiency, ML libraries (scikit-learn, pandas, XGBoost) and NLP transformer techniques, in a fast-moving, cross-functional team. You will validate and deploy models on real clinical data, address missing values and class ...

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 ...

datasets. The ideal candidate should have strong Python and SQL skills and be proficient in data science libraries such as scikit-learn, pandas and XGBoost, as well as transformer-based NLP techniques. We are looking for someone who works well in a fast-moving team and communicates effectively with ...

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 ...

models on Databricks Familiarity 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, Triton Strong communication skills, able to express ideas clearly and collaborate across teams Additional Information Bring ...

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 ...

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 ...

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 ...

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 ...

observability and 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.Experience in areas ...

deliver actionable insights at scale. You will partner with Customer Success, Product, and Engineering, applying time-series forecasting and advanced ML techniques (LightGBM/XGBoost, PyTorch) in a fast-paced environment, with a focus on #J-18808-Ljbffr ...

technical directions, solve complex problems, and help accelerate data-driven decisions across industries. The role requires deep expertise in ML methods (Deep Learning, transformers, XGBoost), strong communication, and ability to manage multi-disciplinary projects with #J-18808-Ljbffr ...

Raffles, Singapore | Posted on 04/06/2026 Experience working with ML platforms such as CML, SparkMLlib, and Python ML libraries (scikit‐learn, XGBoost), including modeldeployment. Design and develop highly scalable, Real time systemsusing Hadoop ecosystem components(Iceberg, Spark, Ozone, Trino, Hive,Ranger, Kafka, Flink and Nifi) Build robust ...

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 ...

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 ...

presentations Adopt data science best-practice e.g. Git/Docker/cloud deployment KEY REQUIREMENTS: Experience with applied machine learning techniques in Python (e.g. xgboost, regression, decision trees) Experience of working collaboratively as part of a data science team, using tools like Git to adhere to established data science … skills High attention to detail Ability to work independently and as part of a team Understanding of classical machine learning concepts and principles (e.g. xgboost, regression, decision trees) INTERVIEW PROCESS: Stage 1: 20 min video call with a member of the hiring team Stage 2: 45 mins live coding task ...