51 to 75 of 95 Feature Engineering Jobs in the UK excluding London

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

offers the chance to make a significant impact within an innovative, tech-driven organisation. You'll work at the forefront of data modelling, analytics engineering, and AI-enablement, helping shape scalable data products that power enterprise reporting, machine learning, and self-service insights. Senior Analytics Engineer/Data Modeller … data consistency across domains. Collaborate with data engineers to support robust ETL/ELT pipelines and maintain end-to-end data lineage. Deploy analytics engineering solutions using dbt, SQL transformations, and CI/CD best practice. Partner with analysts and data scientists to deliver performant and reliable datasets. Implement ...

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. ...

discovery and design of AI strategies, governance models and platform architectures aligned to business outcomes. • Design end-to-end AI solutions, including data ingestion, feature engineering, ML/GenAI models, MLOps and deployment. • Support pre-sales activity, including solution shaping, technical validation, demos and customer presentations. • Bridge multiple … Azure or GCP). • Exposure to private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability ...

discovery and design of AI strategies, governance models and platform architectures aligned to business outcomes. • Design end-to-end AI solutions, including data ingestion, feature engineering, ML/GenAI models, MLOps and deployment. • Support pre-sales activity, including solution shaping, technical validation, demos and customer presentations. • Bridge multiple … Azure or GCP). • Exposure to private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability ...

discovery and design of AI strategies, governance models and platform architectures aligned to business outcomes. • Design end-to-end AI solutions, including data ingestion, feature engineering, ML/GenAI models, MLOps and deployment. • Support pre-sales activity, including solution shaping, technical validation, demos and customer presentations. • Bridge multiple … Azure or GCP). • Exposure to private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability ...