2 of 2 Remote Feature Engineering Jobs in Leeds

Engineer/Data Modeller role offers the chance to make a significant impact within an innovative, tech-driven organisation. You'll work at the forefront of data modelling, analytics engineering, and AI-enablement, helping shape scalable data products that power enterprise reporting, machine learning, and self-service insights. Senior Analytics Engineer/Data Modeller Responsibilities Design, build, and maintain … learning. Ensure documentation, governance, and data consistency across domains. Collaborate with data engineers to support robust ETL/ELT pipelines and maintain end-to-end data lineage. Deploy analytics engineering solutions using dbt, SQL transformations, and CI/CD best practice. Partner with analysts and data scientists to deliver performant and reliable datasets. Implement data quality monitoring, validation processes … and performance optimisation. Support AI initiatives by designing AI marts, feature engineering structures, and ML-ready datasets. Contribute to standardised KPIs, metadata, and a single source of truth for reporting. Work with business teams to translate complex requirements into scalable, high-impact models. Support agile delivery of data products and continuous improvement of modelling standards. Senior Analytics Engineer More ❯

data science and AI modelling solutions to help solve business problems. What you'll do Work with the team to execute data science projects, including data collection, pre-processing, feature engineering, model development, validation, and deployment. Engage with business stakeholders to understand domain-specific challenges and opportunities, and collaborate during development to ensure alignment with requirements. Apply advanced … classification, clustering, time series analysis, natural language processing, and deep learning. Create clear and compelling visualisations to communicate complex analytical findings effectively. Collaborate with stakeholders (including business, product, and engineering) to understand requirements, identify opportunities, and provide data-driven recommendations. Collaborate with cross-functional teams to integrate data science solutions into products and services. Actively participate in knowledge sharing More ❯