15 of 15 Feature Engineering Jobs in the East of England

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 ...

from concept to deployment and maintenance. Utilize programming skills in Python to automate processes and enhance functionality. Work with large datasets for data preprocessing, feature engineering, and model evaluation. Develop and maintain REST APIs and microservices architectures. Monitor, evaluate, and apply governance frameworks for AI/ML models … documentation and effectively communicate complex concepts to both technical and non-technical stakeholders. Required Skills & Qualifications: Minimum 2 years of experience in AI solution engineering, specifically in enterprise environments. Demonstrable experience with Microsoft Azure AI services, including AI Foundry and Microsoft Copilot Studio. Proficiency in Python and familiarity with ...

Focus on hands‐on data science tasks, such as designing experiments Gathering and pre-processing data Building and evaluating models, and collaborating closely with engineering teams to deploy production‐ready solutions Ensure output consistency and quality through collaboration with peers and feedback from reviewers Ideal Qualifications Have strong professional … Have a strong background in one or more of the following areas: exploratory data analysis and statistical inference, machine learning workflows and model evaluation, feature engineering/data preprocessing/data wrangling, or A/B testing/experimentation/causal inference. Application Process Upload resume AI interview ...

Focus on hands‐on data science tasks, such as designing experiments Gathering and pre-processing data Building and evaluating models, and collaborating closely with engineering teams to deploy production‐ready solutions Ensure output consistency and quality through collaboration with peers and feedback from reviewers Ideal Qualifications Have strong professional … Have a strong background in one or more of the following areas: exploratory data analysis and statistical inference, machine learning workflows and model evaluation, feature engineering/data preprocessing/data wrangling, or A/B testing/experimentation/causal inference. Application Process Upload resume AI interview ...

Focus on hands‐on data science tasks, such as designing experiments Gathering and pre-processing data Building and evaluating models, and collaborating closely with engineering teams to deploy production‐ready solutions Ensure output consistency and quality through collaboration with peers and feedback from reviewers Ideal Qualifications Have strong professional … Have a strong background in one or more of the following areas: exploratory data analysis and statistical inference, machine learning workflows and model evaluation, feature engineering/data preprocessing/data wrangling, or A/B testing/experimentation/causal inference. Application Process Upload resume AI interview ...

Focus on hands‐on data science tasks, such as designing experiments Gathering and pre-processing data Building and evaluating models, and collaborating closely with engineering teams to deploy production‐ready solutions Ensure output consistency and quality through collaboration with peers and feedback from reviewers Ideal Qualifications Have strong professional … Have a strong background in one or more of the following areas: exploratory data analysis and statistical inference, machine learning workflows and model evaluation, feature engineering/data preprocessing/data wrangling, or A/B testing/experimentation/causal inference. Application Process Upload resume AI interview ...

Focus on hands‐on data science tasks, such as designing experiments Gathering and pre-processing data Building and evaluating models, and collaborating closely with engineering teams to deploy production‐ready solutions Ensure output consistency and quality through collaboration with peers and feedback from reviewers Ideal Qualifications Have strong professional … Have a strong background in one or more of the following areas: exploratory data analysis and statistical inference, machine learning workflows and model evaluation, feature engineering/data preprocessing/data wrangling, or A/B testing/experimentation/causal inference. Application Process Upload resume AI interview ...

Focus on hands‐on data science tasks, such as designing experiments Gathering and pre-processing data Building and evaluating models, and collaborating closely with engineering teams to deploy production‐ready solutions Ensure output consistency and quality through collaboration with peers and feedback from reviewers Ideal Qualifications Have strong professional … Have a strong background in one or more of the following areas: exploratory data analysis and statistical inference, machine learning workflows and model evaluation, feature engineering/data preprocessing/data wrangling, or A/B testing/experimentation/causal inference. Application Process Upload resume AI interview ...