6 Feature Engineering Jobs in the UK excluding London

leverage technology towards future goals. Your day-to-day responsibilities will include: Leading the UK Data Science Team (8 Direct reports) Collaborate with the engineering and product practices. Team management, including recruitment, onboarding, and developing top talent, ensuring that the team has the skills, resources and support needed to … and validation processes to validate model performance and mitigate risks. Leading the end-to-end process of model development, including data collection pre-processing, feature engineering, model selection, training, evaluation, and validation Who You Are: Have a master’s or PhD in Computer Science, Statistics, Physics, Machine Learning more »

new approach. Diversity is essential to great data teams; we want to hear from candidates from a range of backgrounds and experiences across data engineering, or those looking to refocus. Skills and experience we’re looking for: Proven track record productionising data pipelines at scale Hands-on experience or … understanding of: Python, Spark (e.g., PySpark, Spark tuning, Spark UI); Data Engineering technologies and principles (e.g., Data Lakes, Batch/Streaming); Cloud technologies and principles (e.g., Kubernetes, EMR, S3) Understanding of ML principles (e.g., feature engineering, training/testing, hyperparameters, deep learning, model management) Agile mindset and more »

positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engages them. The Marketing Engineering team at Roku is focused on building the right products and services that help us provide the right communication to the right customers at … ll be doing ML-Infrastructure: Help build a first-class machine learning platform from the ground up which helps manage the entire model lifecycle: feature engineering, model training/evaluation, versioning, deployment/online serving and monitoring prediction quality Data Analysis/Feature Engineering: Apply your more »

extract, transform, load) scripts and code to ensure the ETL process performs optimally. Define and document the pre processing steps, data wrangling techniques and feature engineering undertaken on a given dataset. Design and maintain robust processes to ensure NHSCFA and external stakeholder datasets are separated and securely stored … with system and domain experts to obtain understanding of the data. Please refer to Job Description Person Specification ps Essential oExcellent understanding of data engineering processes, data wrangling methods, models, data structures, and data formats. oJSON, SQL, and XML oWriting robust data pipeline code that can run unattended. oMachine … learning for engineering practices, such as meta driven intelligent ETL and pipeline processes. oStrong skills in relevant programming languages, frameworks, and platforms including, SQL, Python, R, etc. oA strong track record of achievement in data engineering. oExperience/understanding of data lifecycle management frameworks and project management methodology. oExperience more »

extract, transform, load) scripts and code to ensure the ETL process performs optimally. Define and document the pre processing steps, data wrangling techniques and feature engineering undertaken on a given dataset. Design and maintain robust processes to ensure NHSCFA and external stakeholder datasets are separated and securely stored … with system and domain experts to obtain understanding of the data. Please refer to Job Description Person Specification ps Essential oExcellent understanding of data engineering processes, data wrangling methods, models, data structures, and data formats. oJSON, SQL, and XML oWriting robust data pipeline code that can run unattended. oMachine … learning for engineering practices, such as meta driven intelligent ETL and pipeline processes. oStrong skills in relevant programming languages, frameworks, and platforms including, SQL, Python, R, etc. oA strong track record of achievement in data engineering. oExperience/understanding of data lifecycle management frameworks and project management methodology. oExperience more »

doing: Applying scientific methods through experimental design, exploratory data analysis and hypothesis testing to reach robust conclusions Building scalable machine learning pipelines and combining feature engineering with optimisation methods to improve the data product performance Exploring ways of using new data science tools and techniques to address business more »