18 of 18 Feature Engineering Jobs in the UK excluding London

secure AI/ML architectures aligned with enterprise strategy, Omnia principles, and hybrid cloud environments. Design end-to-end AI solutions, including data pipelines, feature engineering, model development, deployment, and operational monitoring. Provide architectural leadership across the full lifecycle, ensuring alignment with DevSecOps, security, and engineering best … practices. Establish standards for model performance monitoring, reliability, risk management, and continuous improvement (MLOps). Collaborate with Enterprise Architecture, engineering leaders, and Army/MoD stakeholders to integrate AI capabilities into existing platforms and services. Evaluate and recommend AI platforms, tools, and frameworks to enable scalable experimentation and production ...

based 3 days per week and comes with a solid Bonus and some fantastic benefits. You’ll be surrounded by Analytics, Data Science and Engineering Colleagues in this meritocratic and highly collaborative team. The Role: You’ll be the most senior hands-on technical contributor within the team … will aid in the design and delivery of complex engineering workloads, provide mentorship to the wider team, and help set and uphold engineering standards across our Databricks platform. The ideal candidate combines deep technical expertise with a natural inclination to bring others along with them. ...

data science and advanced analytics solutions that translate complex business problems into scalable, secure, and high performance data products.This role bridges business stakeholders, data engineering, data science, and IT architecture teams, ensuring solutions are production ready and aligned with enterprise standards.Your ResponsibilitiesSolution & Data Model Design1. Solution Design & Architecture Design … data science solutions including data ingestion, feature engineering, model development, deployment, and monitoring Define logical and physical architectures for analytics platforms, ML pipelines, and AI products Ensure solutions are scalable, reusable, secure, and cost effective Select appropriate ML/AI techniques (e.g., regression, classification, NLP, forecasting, clustering) 2. ...

science and advanced analytics solutions that translate complex business problems into scalable, secure, and high performance data products. This role bridges business stakeholders, data engineering, data science, and IT architecture teams, ensuring solutions are production ready and aligned with enterprise standards. Your Responsibilities Solution & Data Model Design 1. Solution … Design & Architecture Design end to end data science solutions including data ingestion, feature engineering, model development, deployment, and monitoring Define logical and physical architectures for analytics platforms, ML pipelines, and AI products Ensure solutions are scalable, reusable, secure, and cost effective Select appropriate ML/AI techniques (e.g. ...

accessible for self-service analytics and AI/ML model consumption.Collaborate with ML Ops and Data Science teams to define data product standards and feature engineering patterns.Evaluate and lead adoption of emerging Azure and Databricks capabilities - including Microsoft Fabric, OneLake and DirectLake - where they advance the data architecture.Drive … management across business, IT and compliance teams. Excellent communication, collaboration and influencing skills at all levels of an organisation. Experience leading data architecture and engineering teams in an enterprise environment. Ability to define and implement a data strategy aligned with business objectives. Proven track record of delivering enterprise-scale ...

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. ...

investors and data-driven organisations. With data and AI at the core of their product, they are scaling quickly and investing heavily in their engineering and AI capabilities. You will join a collaborative, fully remote team that values transparency, curiosity and speed of execution. The Role You will … small, focused AI team and work closely with engineering to design, build and productionise new AI features across the platform. Key responsibilities include: Designing, training and deploying AI and ML models on complex, large-scale data. Building GenAI solutions using techniques such as RAG and frameworks like LangChain ...

proof-of-concept development using Databricks notebooks, analytical outputs and machine learning techniques to validate product concepts Own technical product definition, including data structures, feature sets, scoring methodologies, model architectures and delivery formats in collaboration with the Product Team Define and monitor technical success metrics (data coverage, refresh latency … needs into technical product requirements Support rapid prototyping and proof-of-concept development using Databricks notebooks and analytics outputs Define product-level data structures, feature sets, scoring outputs and delivery formats in collaboration with the Product Team Product Launch & Performance responsibilities: Define technical success metrics (data coverage, refresh latency ...

translate insights into business impact. Key Responsibilities Design and implement predictive and prescriptive models for MRO AI Solutions. Perform exploratory data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modeling. Communicate findings and recommendations to business stakeholders. Continuously improve models based on feedback ...

long-term operational ownership. As our new Data Scientist (Machine Learning) you will be responsible for: Build predictive, forecasting and anomaly-detection models Perform feature engineering & validation using Python/PySpark Work in Fabric Notebooks, Delta Lakehouse, and AutoML Embed models into production pipelines with our Data Engineering ...

long-term operational ownership. As our new Data Scientist (Machine Learning) you will be responsible for: Build predictive, forecasting and anomaly-detection models Perform feature engineering & validation using Python/PySpark Work in Fabric Notebooks, Delta Lakehouse, and AutoML Embed models into production pipelines with our Data Engineering ...

ownership and production-grade model deployment. The Role As Senior Data Scientist, you will: Own end-to-end ML solutions -from problem framing and feature engineering to deployment, monitoring, and governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models … using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift, and retraining Drive clear documentation, traceability, and governance appropriate for a regulated environment This role requires someone ...

will: Lead and develop a growing Data Science team, setting standards and delivery cadence Own end-to-end ML solutions -from problem framing and feature engineering to deployment, monitoring, and governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models … using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift, and retraining Drive clear documentation, traceability, and governance appropriate for a regulated environment This role requires someone ...

based MMM notebooks to incorporate additional media channels Prepare and validate input data from multiple sources prior to modelling Perform data cleaning, transformation, and feature engineering Run, calibrate, and sense-check MMM model outputs Support model validation and quality checks to ensure outputs are robust and usable Document ...

skills with experience querying large scale relational databases such as Azure SQL or PostgreSQL Experience working with high volume or time based data, including feature engineering Experience with simulation, discrete event simulation, or operations research techniques is highly desirable Ability to communicate complex analysis clearly to non-technical ...

modelling solutions Contribute to model documentation standards and lifecycle governance Own backlog contributions, user stories and acceptance criteria Drive alignment between business stakeholders and engineering team Skills & Competencies Strong knowledge of energy markets, including supply demand fundamentals, storage, flows and pricing Proven background in energy analytics and forecasting, including … scenario modelling Experience with major energy hubs (e.g., TTF, JKM) and cross-commodity linkage Solid understanding of feature engineering, statistical modelling, and ML workflows Strong Python skills (e.g., pandas, NumPy, Jupyter) Strong analytical thinking with the ability to simplify complex concepts If this sounds like a good ...

test hypotheses and inform product decisions. Define success metrics and measure the impact of released product changes. Platform & Data Enablement Work closely with Data Engineering to convert analytical prototypes into production ready pipelines, features and outputs. Ensure product enhancements are designed with data quality, lineage, monitoring and performance … internal and external use. Contribute to improving reuse of shared data assets and reducing duplication across products. Stakeholder Collaboration Work collaboratively with Product, Engineering, Insight and Commercial teams to ensure shared understanding of priorities and constraints. Clearly communicate analytical findings, recommendations and trade-offs to nontechnical stakeholders. Support product ...

prices and select customers, beyond traditional pricing approaches. Work with very large, messy datasets across multiple product lines, leading data exploration, cleaning and feature engineering. Deploy models into production using Python, SQL, Azure ML and an internal deployment platform. Collaborate with pricing, risk and product stakeholders to test ideas … CatBoost, and an interest in geospatial or graph based modelling. Confidence working with large scale, messy, multi source datasets, including complex data cleansing and feature engineering. Experience solving pricing, risk or customer prediction problems and understanding how models drive profit, loss and customer outcomes. How To Apply ...