22 of 22 Permanent Feature Engineering Jobs in the UK excluding London

Machine Learning, Artificial Intelligence, Predictive Analytics, Statistical Modelling, Python, SQL, PySpark, Azure, Databricks, MLflow, GitHub Actions, CI/CD, Time Series Forecasting, Propensity Modelling, Feature Engineering, Data Engineering, Azure Machine Learning, Azure Data Platform, Experiment Design, A/B Testing, Hypothesis Testing, Predictive Modelling, Customer Analytics, Marketing … that improve customer outcomes, enhance commercial performance & support strategic business decision making. Own the complete analytical lifecycle, from initial problem definition & exploratory analysis through feature engineering, model development, deployment, operational monitoring & continuous optimisation. Build sophisticated statistical & machine learning models covering areas such as: * Customer Lifetime Value * Customer Propensity ...

systems: devices that operate autonomously, make decisions in real time, and remain reliable under the constraints that define actual field deployment. The Challenge The engineering challenge is significant. You will be responsible for the complete lifecycle of machine learning models that run on embedded devices. This means: From Sensor … transform this stream into a robust, real-time classification model that runs on hardware with severe constraints on memory, computation, and power. Engineering Under Constraint. Every machine learning decision you make has downstream consequences for embedded systems. A model that requires 512MB of RAM will ...

natural language processing [NLP]/and neural networks [NN]) you will be part of a small, central function that partners closely with product and engineering teams on a single, shared roadmap, with a one‐team mentality throughout. We take a test‐and‐learn approach: real experiments, time‐boxed … data with external reference sources to support faster, better decisions. Deployment & monitoring. Deploying and monitoring machine learning (ML) models in production, with the engineering discipline to catch drift and issues early. Cross‐team support. Occasional collaboration on NLP/NN‐related work led by our existing senior data scientist ...

community. Please do not contact the recruiter directly. Your Role This role focuses on applying data science, statistics, machine learning, graph analytics, and KPI engineering to enable autonomous network intelligence. The AI Data Scientist will work with network telemetry, alarms, performance counters, inventory data, topology data, trouble tickets, service … network operations. Key Responsibilities Analyse large-scale telecom network datasets across RAN, Core, IP, Transport, SD-WAN, Cloud, OSS, and service domains. Develop KPI engineering models for network performance, service quality, fault behaviour, customer impact, capacity, and resilience. Build statistical and machine learning models for anomaly detection, fault prediction ...

Trust. Using Databricks as the primary development environment, you will build reproducible, auditable analytical workflows in SQL and Python, including data preparation, quality checks, feature engineering and modelling. You will also design and deliver reporting products and dashboards (for example in Power BI) to communicate clear, actionable insight … analytical and predictive models on curated Trust datasets. This includes full responsibility for data preparation activities such as data quality checks, cleansing, preprocessing and feature engineering, ensuring all work follows agreed definitions and is reproducible and auditable. The postholder will create reporting products and dashboards (for example using ...

positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them. Within Advertising Engineering, the MarTech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience … pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can work effectively with engineering, product, data science, and commercial stakeholders across Roku. The successful candidate will display a balance of hard and soft skills, including the ability to respond ...

positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them. Within Advertising Engineering, the MarTech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience … using code for statistical analysis and tool building, using both general‐purpose software and statistical languages. What You’ll Be Doing Data Analysis/Feature Engineering: Apply your expertise to identify and calculate features that can be leveraged by multiple use cases as well as models. Train Machine ...

powered products and customer-facing features • Apply machine learning techniques to solve complex business problems • Support experimentation through modelling, statistical testing and evaluation • Conduct feature engineering and feature analysis to improve model performance • Work closely with Product, Engineering and Analytics teams on high-impact initiatives • Build ...

Work With Building and deploying AI and Machine Learning solutions Designing and implementing end-to-end AI and ML pipelines, from data acquisition and feature engineering through to deployment and optimisation Developing scalable ML pipelines and engineering frameworks AI model training, evaluation, optimisation and deployment Cloud-native … stakeholders to understand business challenges and translate requirements into AI solutions Working closely with technical and non-technical teams throughout programme delivery Cross-functional engineering, architecture and data teams Agile software development and delivery methodologies Exploring and adopting emerging AI technologies and approaches to drive innovation and business value ...

NumPy, scikit-learn and relevant statistical or machine learning packages Hands-on experience with machine learning frameworks and approaches, including supervised learning, unsupervised learning, feature engineering, modelselectionand model validation Practical experience building Generative AI and LLM-based solutions, including prompt engineering, embeddings, vector databases, RAG, grounding, reranking ...

NumPy, scikit-learn and relevant statistical or machine learning packages Hands-on experience with machine learning frameworks and approaches, including supervised learning, unsupervised learning, feature engineering, modelselectionand model validation Practical experience building Generative AI and LLM-based solutions, including prompt engineering, embeddings, vector databases, RAG, grounding, reranking ...

play a key role in designing, developing and deploying AI and Machine Learning solutions, working across the full ML lifecycle from data preparation and feature engineering through to model deployment and optimisation. Working with Python, SQL and leading ML frameworks, you'll build scalable pipelines, develop and evaluate ...

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. ...

Build and maintain scalable data science products, including predictive models, forecasting solutions, segmentation, recommendation engines and experimentation frameworks that support business decision-making. Data Engineering & Model Productionisation: Develop robust analytical datasets and machine learning pipelines using Databricks, Python, SQL and Spark, ensuring solutions are scalable, reliable and production-ready. … learning workflows using Databricks, Spark or similar large‐scale data processing technologies. Machine Learning & Statistical Expertise: Deep understanding of supervised and unsupervised machine learning, feature engineering, model evaluation, experimentation and performance monitoring techniques. Retail & Commercial Analytics: Experience applying data science in retail, consumer, grocery, apparel or other high ...

Data Science team of a large, established financial services business. The company has invested in its data platform and is building a dedicated ML Engineering capability to get more models into production. You'll work on real business problems, using large and varied datasets to develop models that … initial experimentation. You should be comfortable with: Python and common data science libraries. SQL and working with large datasets. Statistical modelling and machine learning. Feature engineering, model selection and evaluation. Writing clear, maintainable and testable code. Git-based development workflows. Working in a cloud environment such as Azure ...

optimization techniques for LLM-based agents Resource-constrained AI model deployment Vector databases and semantic search (e.g., Pinecone, Weaviate, Milvus, Qdrant , and ChromaDB ) Prompt engineering for efficient agent reasoning LLM fine-tuning and instruction optimization Graph databases for network topology and context management Feature engineering for network … deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion. Make it real | www.capgemini.com ...

Machine Learning solutions, and explain your approach and results End-to-end delivery mindset, you can take a problem from definition through data preparation, feature engineering, model training/validation, and performance monitoring Cloud fundamentals (GCP preferred), youve used cloud native tools and are keen to build deeper ...

here at Sky. Role/Team overview We are seeking an AI Specialist to design, build, and operationalise intelligent systems that enhance Site Reliability Engineering (SRE) platforms and automate large-scale infrastructure operations. This role has a strong emphasis on reliability, scalability, and operational efficiency. You will work closely … with SRE, platform, and cloud engineering teams, within a global technology support organisation to embed AI-driven decision-making, predictive analytics, and autonomous remediation into infrastructure platforms. Whatyou’lldo Infrastructure Automation at Scal e Design and deploy AI-powered automation frameworks for incident response and remediation (self-healing systems ...

here at Sky. Role/Team overview We are seeking an AI Specialist to design, build, and operationalise intelligent systems that enhance Site Reliability Engineering (SRE) platforms and automate large-scale infrastructure operations. This role has a strong emphasis on reliability, scalability, and operational efficiency. You will work closely … with SRE, platform, and cloud engineering teams , within a global technology support organisation to embed AI-driven decision-making, predictive analytics, and autonomous remediation into infrastructure platforms . What youll do Infrastructure Automation at Scal e Design and deploy AI-powered automation frameworks for incident response and remediation (self ...

then scale into production Shape problem definitions with stakeholders in ambiguous environments Bring best practices from adjacent industries into a high-performance setting Data Engineering & Architecture Design/maintain pipelines integrating telemetry/timing, video/image, event operations, and digital/commercial engagement data Develop APIs/services … secure-by-design delivery with cyber teams What we're looking for Essentials 5-10 years' experience in data science/AI/ML engineering Strong Python Production ML deployment experience (end-to-end) Strong SQL + modern data warehouse experience Cloud familiarity + containerisation/orchestration Streaming data ...

real-world GenAI and ML solutions across the entire LexisNexis business. Our work powers smarter decisions for Product, Sales, Finance, Marketing, Customer Success, and Engineering-everything from predictive models to enterprise GenAI apps to automation that transforms how teams operate . We are data science generalists who love variety. … designing a new GenAI workflow, the next it is deploying a model into Salesforce or engineering a pipeline in Databricks. We own our projects end-to-end and partner directly with stakeholders to deliver solutions that get used and make a measurable difference. If you want to experiment, build ...

typically lead a team or the solution delivery effort, demonstrating technical excellence through leading by example. You could be providing technical support, leading an engineering team or working across multiple teams as a subject matter expert who is critical to the success of a large programme of work. Your … deployments. Shape team behaviour for writing specifications and acceptance criteria, estimating stories, sprint planning and documentation. Actively define and evolve PA’s data engineering standards and practices, ensuring we maintain a shared, modern and robust approach. Lead and influence technical discussions with client stakeholders to achieve the collective ...