26 to 50 of 120 Feature Engineering Jobs in the UK excluding London

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

be considered for this position. ABOUT THIS OPPORTUNITY A great opportunity has arisen for a Data Engineer to work within the Personalised Experiences and Communications Platform to join product engineering cross functional teams. As a Data Engineer your responsibilities will be delivering the highest quality data capability, drawing upon your engineering expertise, whilst being open minded to the … opportunities the cloud provides. What you'll be doing... Building reusable data pipelines at scale, work with structured and unstructured data, and feature engineering for machine learning or curate data to provide real time contextualise insights to power our customers journeys. Using industry leading toolsets, as well as evaluating exciting new technologies to design and build scalable real … Azure, Teradata, SQL server) you'll get to work building capabilities with horizon-expanding exposure to a host of wider technologies and careers in data. Helping in adopting best engineering practices like Test Driven Development, code reviews, Continuous Integration/Continuous Delivery etc for data pipelines. Mentoring other engineers to deliver high quality and data led solutions for our More ❯

team at Abcam is at the forefront of developing next-generation AI solutions for a wide range of life science questions, including fundamental biological topics like antibody development, genetic engineering of cell lines, etc. We are uniquely positioned with proven AI benefits, strong data and technology offerings, state-of-the-art labs, and expert interdisciplinary teams. As Senior AI … standardization, documentation, and software development lifecycle. Improve the technical quality and reliability of AI solutions through rigorous testing and validation. Implement frameworks for scalable data ingestion by AI applications. Feature engineer data for performance and efficiency optimization of AI applications. Collaborate closely with TechOps, Data Engineering, Architecture, and Cyber Security teams for seamless technology integration. Work with Data More ❯

if not all, of the following areas: Statistics, Machine Learning, Deep Learning & GenAI You will have experience at each process within data science, problem definition, data acquisition & wrangling, modelling, feature engineering and deployment What’s equally relevant is programming knowledge and a gift for coding using: Python, SQL, or Spark You’ll also need the capability to deliver More ❯

What you will be doing... We're seeking a Senior Data Scientist to join our Jet2 Data Science team, specifically to work with our Airline Engineering team based at Leeds Bradford International Airport. Our Senior Data Scientist will be responsible for the delivery of key initiatives capable of realising significant value, combining insights gained from multiple large data sources … with the contextual understanding and experience of our colleagues across the business. This exciting new role focuses on driving innovation within our engineering and maintenance operations, playing a critical role in executing our engineering data and analytics strategy. You'll join an established and growing team of Data Science professionals and be based within Engineering Technologies, who … are leveraging the use of data-driven insights and innovative technologies to optimise our Engineering & Maintenance operations. As our Senior Data Scientist , you'll have access to a wide range of benefits including: Hybrid working (we're in the office 2 days per week) Annual pay reviews Access to a generous discretionary profit share scheme What you'll be More ❯

Social network you want to login/join with: Senior Data Scientist (Engineering Technologies), Leeds col-narrow-left Client: Jet2.com Location: Leeds, United Kingdom Job Category: Other - EU work permit required: Yes col-narrow-right Job Reference: 9f34c00ffce8 Job Views: 7 Posted: 22.06.2025 Expiry Date: 06.08.2025 col-wide Job Description: We're seeking a Senior Data Scientist to join … our Jet2 Data Science team, specifically to work with our Airline Engineering team based at Leeds Bradford International Airport. Our Senior Data Scientist will be responsible for the delivery of key initiatives capable of realising significant value, combining insights gained from multiple large data sources with the contextual understanding and experience of our colleagues across the business. This exciting … new role focuses on driving innovation within our engineering and maintenance operations, playing a critical role in executing our engineering data and analytics strategy. You'll join an established and growing team of Data Science professionals and be based within Engineering Technologies, who are leveraging the use of data-driven insights and innovative technologies to optimise our More ❯

Principal ML/AI Engineer - Python | Greenfield AI Platform (Contract) We are seeking a Principal/Senior AI/ML Engineer with a strong foundation in software engineering and Python development, to join a globally renowned organisation at the forefront of AI innovation. This is a rare chance to work on greenfield AI/ML projects, delivering transformative solutions … systems using Python and modern frameworks. Lead technical design discussions and influence system-level decisions across greenfield initiatives. Build and scale end-to-end ML pipelines, including data ingestion, feature engineering, model training, and deployment. Champion best practices in software engineering: CI/CD, testing, containerisation, version control, and code quality. Collaborate with cross-functional teams including … data scientists, platform engineers, and product stakeholders to align AI solutions with business goals. Experience Strong commercial experience in Python with a deep understanding of software engineering principles. Demonstrated expertise in building ML systems in production environments (not just notebooks or research). Proven leadership experience in either a senior IC or tech lead/managerial capacity. Familiarity with More ❯

customer data, understanding and appreciating the underlying domain, carrying out analysis, and integrating or developing new techniques for implementation and delivery as part of our product offerings. This includes feature engineering, applying varying models, testing, and validation, and best practices for use for customers. Responsibilities: Development of predictive models using time series, geospatial and environmental sensor data. Designing … scalable feature engineering and data transformation processes tailored to sewer data. Collaboration with wastewater domain experts to guide bespoke modelling approaches to address industry issues. Build required product and custom features while seeking to maximise reuse of existing code and features. Engaging with customers to understand contextual requirements of projects, present findings and lead integration into StormHarvester product. … AI principles and application in implementation and practical delivery. Experienced in Python development and tooling including Pandas, Scikit-learn or equivalent. A third level qualification in Computer Science, Software Engineering, Data Science or other related discipline. Experience with data exploration and visualisation. A theoretical and practical foundation of core analytics and machine learning principles and experience working with large More ❯

markets. Build, train, and refine ML-based models for algorithmic trading. Collaborate with a skilled international team. Must-Have: Education: Bachelor’s degree or higher in Computer Science, Software Engineering, or related fields. Experience: Building production-grade trading system based on ML algorithms. Expertise in financial data analysis, feature engineering, back-testing, and deploying models. Developing crypto More ❯

markets. Build, train, and refine ML-based models for algorithmic trading. Collaborate with a skilled international team. Must-Have: Education: Bachelor’s degree or higher in Computer Science, Software Engineering, or related fields. Experience: Building production-grade trading system based on ML algorithms. Expertise in financial data analysis, feature engineering, back-testing, and deploying models. Developing crypto More ❯

markets. Build, train, and refine ML-based models for algorithmic trading. Collaborate with a skilled international team. Must-Have: Education: Bachelor’s degree or higher in Computer Science, Software Engineering, or related fields. Experience: Building production-grade trading system based on ML algorithms. Expertise in financial data analysis, feature engineering, back-testing, and deploying models. Developing crypto More ❯

be considered for this position. ABOUT THIS OPPORTUNITY A great opportunity has arisen for a Data Engineer to work within the Personalised Experiences and Communications Platform to join product engineering cross functional teams. As a Data Engineer your responsibilities will be delivering the highest quality data capability, drawing upon your engineering expertise, whilst being open minded to the … opportunities the cloud provides. What you'll be doing Building reusable data pipelines at scale, work with structured and unstructured data, and feature engineering for machine learning or curate data to provide real time contextualise insights to power our customers journeys. Using industry leading toolsets, as well as evaluating exciting new technologies to design and build scalable real … Azure, Teradata, SQL server) you'll get to work building capabilities with horizon-expanding exposure to a host of wider technologies and careers in data. Helping in adopting best engineering practices like Test Driven Development, code reviews, Continuous Integration/Continuous Delivery etc for data pipelines. Mentoring other engineers to deliver high quality and data led solutions for our More ❯

Options: Hybrid Working, Job Share Job Description Summary: A great opportunity has arisen for a Data Engineer to work within the Personalised Experiences and Communications Platform to join product engineering cross functional teams. As a Data Engineer, your responsibilities will include delivering the highest quality data capability, drawing upon your engineering expertise, whilst being open-minded to the … opportunities the cloud provides. What you’ll be doing... Building reusable data pipelines at scale, working with structured and unstructured data, and feature engineering for machine learning or curating data to provide real-time contextual insights to power our customers' journeys. Using industry-leading toolsets, as well as evaluating exciting new technologies to design and build scalable real … Azure, Teradata, SQL server) you’ll get to work building capabilities with horizon-expanding exposure to a host of wider technologies and careers in data. Helping in adopting best engineering practices like Test Driven Development, code reviews, Continuous Integration/Continuous Delivery for data pipelines. Mentoring other engineers to deliver high-quality and data-led solutions for our Bank More ❯

grow by tackling complex technical challenges. Responsibilities Design, build, and maintain AI systems and tools using machine learning and large language models (LLMs), with a strong focus on prompt engineering and model fine-tuning. Collaborate with cross-functional teams to identify opportunities for AI and automation across the product suite. Develop scalable pipelines for data ingestion, model training, evaluation … operating as a senior level engineer within a product or SaaScompany Proven experience with Python and ML libraries such as TensorFlow or PyTorch. Experience working with LLMs (Gemini), prompt engineering, and reinforcement learning from human feedback (RLHF). Experience with LangChain for building LLM applications with RAG pipelines and agent workflows. Practical understanding of vector search, embeddings, and retrieval … generation (RAG). Experience building and deploying machine learning models into production environments. Familiarity with MLOps tools and practices (Vertex AI). Understanding of data pipelines, data preparation, and feature engineering. Bonus Points for: Hands-on experience with prompt tuning, fine-tuning LLMs, or adapting open-source models for specific use cases. Hands-on experience with AlloyDB or similar. More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

Director, Principal AI/NLP Engineer Introduction to Role: Are you ready to apply your AI/NLP engineering skills in a place where curiosity thrives and groundbreaking work is done? Join our AI Engineering team at AstraZeneca in Cambridge (UK) and be part of a company that follows the science unlike anywhere else! At AstraZeneca, we connect … you will develop and deploy NLP models and algorithms to extract insights from unstructured text data. You will design and implement end-to-end NLP pipelines, including data preprocessing, feature engineering, model training, and evaluation. Collaborating with multi-functional teams, you will understand client requirements and develop customized NLP solutions to address their specific needs. By staying up … Communication and Teamwork: Superior teamwork and communication skills, with a demonstrated ability to mentor and lead teams. - Hands-on Data Expertise: Extensive hands-on experience with data preprocessing techniques, feature engineering, and model evaluation. - Proven Project Delivery: A proven track record of successfully delivering NLP projects in academia or/and industry. - Experience with LLMs and Generative AI More ❯

AI/ML use cases. You'll work with diverse datasets spanning prepaid, financial services, gambling, and payments, supporting business-critical decisions with high-quality, well-structured data. While engineering will be your focus, you'll also need to collaborate across analytics and product functions-comfortable switching between roles to meet team goals. This role includes occasional global travel … the role: Data Pipeline Development: Build and maintain batch and streaming pipelines using Azure Data Factory and Azure Databricks. Data Categorisation & Enrichment: Structure unprocessed datasets through tagging, standardisation, and feature engineering. Automation & Scripting: Use Python to automate ingestion, transformation, and validation processes. ML Readiness: Work closely with data scientists to shape training datasets, applying sound feature selection techniques. … Data Validation & Quality Assurance: Ensure accuracy and consistency across data pipelines with structured QA checks. Collaboration: Partner with analysts, product teams, and engineering stakeholders to deliver usable and trusted data products. Documentation & Stewardship: Document processes clearly and contribute to internal knowledge sharing and data governance. Platform Scaling: Monitor and tune infrastructure for cost-efficiency, performance, and reliability as data More ❯

database networking, maintaining data security, and configuring user access and authentication protocols in a modern data warehouse. Proficiency in Python, git, SQL, AWS and Snowflake. Strong understanding of data engineering best practices, and experience with data pipelines, data structures, data platforms, data integration and data governance. It would be a plus if you also possess previous experience in: Experience … building and managing AWS cloud infrastructure. Experience in feature engineering for data consumption by AI Applications. Join our winning team today. Together, we'll accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science More ❯

sources. • Translating domain knowledge into useful features and model inputs in close collaboration with subject matter experts. • Use both structured and unstructured data sources to carry out data wrangling, feature engineering, and root cause analysis. • Monitor model performance, retrain as necessary, and make sure models continue to be precise and understandable in real-world settings. • Ensure compliance to More ❯

Machine Learning Engineering Manager (Operations) Join to apply for the Machine Learning Engineering Manager (Operations) role at THG Ingenuity . About THG Ingenuity THG Ingenuity is a fully integrated digital commerce ecosystem, designed to power brands without limits. Our global end-to-end tech platform includes three products: THG Commerce, THG Studios, and THG Fulfilment. Each offers a … goals. Oversee the entire lifecycle of ML projects from conception to deployment and monitoring. Guide the team in building, training, and deploying models. Ensure best practices in data preparation, feature engineering, and model validation. Establish workflows for deployment, monitoring, and scaling of models. Qualifications Proven experience as a Machine Learning Engineer, with leadership experience in deploying models in More ❯

skills – even better if these skills have been applied to threat detection, malware analysis, phishing and/or abuse detection. Experience building production-grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring. Experience designing and implementing anomaly detection, classification, clustering, and retrieval across vision and language models, ideally for identifying cyber threats (URLs, domains … fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI services at scale, particularly on AWS via Terraform. The package offered to the Senior/Principal AI Engineer will consist of More ❯

with a strong analytical background, capable of maintaining technical contributions while managing a team. Your qualifications include: Experience delivering data science initiatives from concept to production, including data preprocessing, feature engineering, and model evaluation. Strong communication skills for explaining complex concepts to business stakeholders. Proficiency in Python or similar tools, strong SQL skills, and experience with data visualization More ❯

CD pipelines to deploy machine learning models into production, ensuring scalability, reliability, and continuous performance monitoring with automated retraining workflows. You will also implement version control for models and feature sets to ensure reproducibility, traceability, and compliance with best practices. Using Azure and infrastructure-as-code tools (e.g., Azure Bicep, Terraform) you will automate and manage infrastructure for data … pipelines, machine learning model training, and serving. Additionally, you will establish infrastructure and engineering patterns to feature engineering and reuse across suite of models. Developing workflows for model validation, testing, and deployment, fully integrated with CI/CD systems, while enhancing resource utilization, to enable distributed processing, and optimize workflows for scalability, including GPU/TPU acceleration. … have experience managing machine learning infrastructure in production, working with infrastructure-as-code tools such as Azure Bicep, Terraform, ARM, CloudFormation or similar, and good practical experience in data engineering, for machine learning or general analytics use case. Additionally, having experience with Kubernetes or other platforms for containerized applications as well as working with orchestration systems such as Apache More ❯

Sports Modelling to join their Research & Development team. You will play a key role in enhancing and developing state-of-the-art sports models. This position involves data science, engineering, software development, and mathematics , offering the opportunity to work on impactful machine learning solutions within the iGaming industry. Key Responsibilities Build and maintain robust datasets for machine learning models. … Skills & Qualifications Solid experience with machine learning , especially neural networks . Strong programming skills, preferably in Python ; knowledge of Matlab is a plus. Expertise in data shaping, preprocessing, and feature engineering . Excellent command of English , both written and spoken. Prior experience in the iGaming or sports modelling industry is a strong advantage. What’s on Offer An More ❯