1 to 25 of 108 Permanent Feature Engineering Jobs in England

working across the full ML lifecycle—from design through to production—in a modern, AWS-based environment. You'll be part of an engineering and data team tackling projects like LLM development, intelligent automation, semantic search, and recommendation systems. There's real scope here to influence how MLOps … doing: Building and deploying ML models and LLM applications Fine-tuning large language models for specific use cases Working with prompt engineering and RAG systems Creating end-to-end ML pipelines—ingestion, feature engineering, deployment Developing LLM-powered tools: chatbots, automation, content generation Implementing MLOps practices: versioning ...

role in developing, experimenting with and deploying advanced AI and machine learning products that deliver clear commercial value. Reporting to the Analytics Engineering Manager, you will work across the full ML lifecycle; from exploratory research and rapid prototyping to production deployment and ongoing optimisation. You will combine strong experimentation … skills with hands-on engineering capability, delivering practical AI solutions such as forecasting engines, personalisation models, segmentation, attribution and advanced revenue optimisation. You will also innovate with emerging technologies including LLMs, Agentic AI and automation frameworks, shaping how AI is adopted across the organisation. You will collaborate closely with ...

role in developing, experimenting with and deploying advanced AI and machine learning products that deliver clear commercial value. Reporting to the Analytics Engineering Manager, you will work across the full ML lifecycle; from exploratory research and rapid prototyping to production deployment and ongoing optimisation. You will combine strong experimentation … skills with hands-on engineering capability, delivering practical AI solutions such as forecasting engines, personalisation models, segmentation, attribution and advanced revenue optimisation. You will also innovate with emerging technologies including LLMs, Agentic AI and automation frameworks, shaping how AI is adopted across the organisation. You will collaborate closely with ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...

intensive and cannot be solved manually within reasonable timeframes (days/weeks) Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility … Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving ...