26 to 36 of 36 Remote XGBoost Jobs

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 ...

End Date Friday 09 October 2026 Salary Range £72,702 - £80,780 Location(s) Bristol, Chester or Manchester Hours Full time, 35 hours per week Working Pattern Our work style is hybrid, which involves spending ...

End Date Friday 09 October 2026 Salary Range £72,702 - £80,780 Location(s) Bristol, Chester or Manchester Hours Full time, 35 hours per week Working Pattern Our work style is hybrid, which involves spending ...

End DateFriday 09 October 2026Salary Range72,702 - 80,780We support flexible working – click here for more information on flexible working optionsFlexible Working OptionsJob ShareJob Description Summary.Job DescriptionJOB TITLE: Senior Machine Learning Engineer SALARY: 72,702 ...

End DateFriday 09 October 2026Salary Range72,702 - 80,780We support flexible working – click here for more information on flexible working optionsFlexible Working OptionsJob ShareJob Description Summary.Job DescriptionJOB TITLE: Senior Machine Learning Engineer SALARY: 72,702 ...

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 ...

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. ...

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. ...

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 ...

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 ...