8 of 8 Remote/Hybrid Feature Engineering Jobs in London

analytics environment. This role will focus on building and optimising SAS-based models, supporting the full model development lifecycle from data preparation and feature engineering through to testing, validation, and production deployment. Key Responsibilities * Design, develop, and enhance statistical, predictive, and pricing models using SAS * Build modelling datasets … feature engineering pipelines, and variable transformations * Develop SAS programs using: o Base SAS o SAS Macros o Data Step o SAS SQL * Support automated model execution, scoring, and monitoring processes * Conduct model testing, validation, back-testing, and performance analysis * Analyse large datasets to identify trends, patterns, and business ...

deploy ML models for use cases like fraud detection, risk modeling, and customer analytics Build predictive, classification, clustering, and recommendation models Perform data preprocessing, feature engineering, and model evaluation Design scalable ML pipelines and production-grade solutions Develop NLP and GenAI solutions (RAG, embeddings, LLM-based applications) Deploy … statistical modeling Hands-on experience with Scikit-learn, Pandas, NumPy, XGBoost/LightGBM Experience with TensorFlow/PyTorch/Keras Solid understanding of feature engineering, model tuning, and evaluation metrics Experience with SQL and data handling Knowledge of MLOps (CI/CD, model deployment, monitoring) Experience deploying ...

hire has very meaningful impact.They are looking for a Senior Data Scientist to lead the predictive analytics capability and their critical programme.You’ll design feature engineering pipelines, select and validate classification and regression models, and establish rigorous evaluation methodology (targeting AUC-ROC 0.85) across a 300M+ point education … explainable and production-ready.Core Responsibilities: Predictive Model Development : Build and validate supervised learning models (classification & regression) using complex, multi-source, time-series-influenced data. Feature Engineering : Design scalable feature pipelines across attendance, behaviour, wellbeing, assessment and SEND datasets. Evaluation & Methodology : Establish rigorous evaluation frameworks including ...

building, and deploying scalable machine learning solutions to enable advanced analytics, automation, and decision-making across complex government systems. This is a hands-on engineering role, working closely with data scientists, analysts, architects, and product teams to productionise models, build data pipelines, and embed ML capabilities into live services. … Synapse) Experience in AWS environments is beneficial Experience with MLOps practices and tools (CI/CD pipelines, model monitoring, versioning) Strong understanding of data engineering concepts (ETL pipelines, data lakes, feature engineering) Experience working with large-scale structured and unstructured datasets Knowledge of AI ethics, bias mitigation ...

taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI. Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization … inference, experimentation, monitoring, and continuous improvement. Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems. Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical ...

problem definition through to deployment in live environments.* Design, build, and deploy machine learning models within Pega-based decisioning platforms.* Lead model development across feature engineering, training, validation, and ongoing performance monitoring.* Work closely with application and logic developers to embed models into operational decision workflows.* Develop statistical ...

Pega CDH adaptive models Strong MLB/RTIM/arbitration logic knowledge Advanced Python & ML development A/B testing, uplift measurement, model governance Feature engineering & real-time vs batch decisioning Git, Agile, cross-functional collaboration NBA Decisioning Specialist Deliver decisioning use cases and personalisation strategies. Key Skills ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...