1 to 25 of 84 Permanent Feature Engineering Jobs in England

working across the full ML lifecycle—from design through to production—in a modern, AWS-based environment. You'll be part of an engineering and data team tackling projects like LLM development, intelligent automation, semantic search, and recommendation systems. There's real scope here to influence how MLOps … doing: Building and deploying ML models and LLM applications Fine-tuning large language models for specific use cases Working with prompt engineering and RAG systems Creating end-to-end ML pipelines—ingestion, feature engineering, deployment Developing LLM-powered tools: chatbots, automation, content generation Implementing MLOps practices: versioning ...

evaluate predictive models using statistical, machine learning, and analytical techniques 🛠 Support the design and maintenance of data pipelines — from data collection and cleaning to feature engineering 📊 Build visualisations, dashboards, and reports that turn data into clear business insights 🤝 Collaborate with cross-functional teams including analysts, engineers, and product … Python skills and exposure to analytics/ML frameworks such as pandas, NumPy, scikit-learn, or TensorFlow 🧮 Solid understanding of statistical methods, data wrangling, feature engineering, and model evaluation 🗄 Confidence working with SQL and large datasets ☁️ Familiarity with cloud platforms (AWS, GCP, or Azure) and version control tools ...

evaluate predictive models using statistical, machine learning, and analytical techniques 🛠 Support the design and maintenance of data pipelines — from data collection and cleaning to feature engineering 📊 Build visualisations, dashboards, and reports that turn data into clear business insights 🤝 Collaborate with cross-functional teams including analysts, engineers, and product … Python skills and exposure to analytics/ML frameworks such as pandas, NumPy, scikit-learn, or TensorFlow 🧮 Solid understanding of statistical methods, data wrangling, feature engineering, and model evaluation 🗄 Confidence working with SQL and large datasets ☁️ Familiarity with cloud platforms (AWS, GCP, or Azure) and version control tools ...

models that AstraZeneca will own and evolve. Expect hands‐on supervised learning for enrollment timelines and site‐level predictions (e.g., gradient boosting), TA‐specific feature engineering, protocol similarity, statistical sampling and optimization under constraints, and rigorous monitoring (drift, performance, stability). You’ll integrate internal data with external … Establish performance tracking (e.g., MAE/RMSE, calibration, lift), stability checks, and drift detection, document rationale for overrides and decisions. Data integration and feature engineering Build a single source of truth linking internal operational data with external sources Pressure test model outputs and fine-tine base ...

region and Tech Unicorn. Position Summary: We are looking for a highly experienced Data Scientist with foundational skills in Machine Learning Engineering, and Generative AI to join our innovative AI & Data Science team. The ideal candidate will bring expertise in advanced predictive modeling, scalable data solutions, and integrating … monitoring systems to ensure performance, reliability, and fairness. Develop and optimize advanced analytics and visualization frameworks to support decision-making at scale. Collaborate with engineering teams to ensure production-grade scalability, low latency, and operational resilience of deployed models. Integrate trust and explainability into model design, generate confidence scores ...

region and Tech Unicorn. Position Summary: We are looking for a highly experienced Data Scientist with foundational skills in Machine Learning Engineering, and Generative AI to join our innovative AI & Data Science team. The ideal candidate will bring expertise in advanced predictive modeling, scalable data solutions, and integrating … monitoring systems to ensure performance, reliability, and fairness. Develop and optimize advanced analytics and visualization frameworks to support decision-making at scale. Collaborate with engineering teams to ensure production-grade scalability, low latency, and operational resilience of deployed models. Integrate trust and explainability into model design, generate confidence scores ...

region and Tech Unicorn. Position Summary: We are looking for a highly experienced Machine Learning/Data Scientist with foundational skills in Machine Learning Engineering, and Generative AI to join our innovative AI & Data Science team. The ideal candidate will bring expertise in advanced predictive modeling, scalable data solutions … monitoring systems to ensure performance, reliability, and fairness. Develop and optimize advanced analytics and visualization frameworks to support decision-making at scale. Collaborate with engineering teams to ensure production-grade scalability, low latency, and operational resilience of deployed models. Integrate trust and explainability into model design, generate confidence scores ...

region and Tech Unicorn. Position Summary: We are looking for a highly experienced Machine Learning/Data Scientist with foundational skills in Machine Learning Engineering, and Generative AI to join our innovative AI & Data Science team. The ideal candidate will bring expertise in advanced predictive modeling, scalable data solutions … monitoring systems to ensure performance, reliability, and fairness. Develop and optimize advanced analytics and visualization frameworks to support decision-making at scale. Collaborate with engineering teams to ensure production-grade scalability, low latency, and operational resilience of deployed models. Integrate trust and explainability into model design, generate confidence scores ...

Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic … Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including ...

Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic … Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including ...

Responsibilities Develop, train, and evaluate machine learning models to solve real-world business problems. Support the full ML lifecycle—from data exploration and feature engineering to deployment and monitoring. Work with large datasets using modern data tooling and cloud platforms. Implement scalable ML pipelines and contribute to automation … initiatives. Collaborate with cross-functional teams to translate client requirements into technical solutions. Stay updated with the latest advancements in ML, AI, and data engineering practices. About You A degree (BSc, MSc, or PhD) in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related STEM field. Strong ...

Responsibilities Develop, train, and evaluate machine learning models to solve real-world business problems. Support the full ML lifecycle—from data exploration and feature engineering to deployment and monitoring. Work with large datasets using modern data tooling and cloud platforms. Implement scalable ML pipelines and contribute to automation … initiatives. Collaborate with cross-functional teams to translate client requirements into technical solutions. Stay updated with the latest advancements in ML, AI, and data engineering practices. About You A degree (BSc, MSc, or PhD) in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related STEM field. Strong ...

responsibilities: Design, develop, and deploy AI/ML models and solutions, including LLMs and GenAI. Perform feature engineering and selection to optimize model performance. Select and implement appropriate AI/ML algorithms, including supervised, unsupervised, and reinforcement learning models. Deploy models to production environments, ensuring robustness and scalability. ...

real AI projects, learning from experts, and gaining hands-on experience with modern AI tools, models, and data pipelines. Whether you studied Computer Science, Engineering, Maths, Data Science, or a related field, if you have a passion for AI and a hunger to learn — we want to hear from … TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance ...

this role, you will take ownership of complex models and pipelines, influence technical direction, and mentor less experienced team members while working closely with engineering and product teams. What You'll Do Design, build, and deploy scalable ML and AI solutions for production environments. Lead model development, evaluation … frameworks such as TensorFlow, PyTorch, or scikit-learn. Experience working with LLMs, NLP, computer vision, or recommendation systems. Solid understanding of data pipelines, feature engineering, and model evaluation. Experience with cloud platforms (AWS, Azure, or GCP) and ML deployment strategies. Strong communication skills and experience mentoring or leading ...

this role, you will take ownership of complex models and pipelines, influence technical direction, and mentor less experienced team members while working closely with engineering and product teams. What You’ll Do Design, build, and deploy scalable ML and AI solutions for production environments. Lead model development, evaluation … such as TensorFlow, PyTorch, or scikit-learn . Experience working with LLMs, NLP, computer vision, or recommendation systems . Solid understanding of data pipelines, feature engineering, and model evaluation. Experience with cloud platforms (AWS, Azure, or GCP) and ML deployment strategies. Strong communication skills and experience mentoring ...

ability to gut them and work with them past just surface-level functionality. Experience with the full model development lifecycle, from data preprocessing and feature engineering to model validation. Degree in Computer Science, Machine Learning, Computational Chemistry, or equivalent industry experience. Nice To Haves Prior experience in computational ...

ability to gut them and work with them past just surface-level functionality. Experience with the full model development lifecycle, from data preprocessing and feature engineering to model validation. Degree in Computer Science, Machine Learning, Computational Chemistry, or equivalent industry experience. Nice To Haves Prior experience in computational ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...