21 Feature Engineering Jobs in the UK

Software Engineering Permanent - Full Time Salford, GB, M50 2HQ BBC PUBLIC SERVICE B'CAST Job Closing Date: 21/05/2024 THE ROLE Package Description Band: D £55,000 - £65,000 per annum dependent on experience Contract type: permanent Location: Salford (hybrid working – 2 days in office per … underrepresented groups. If you require any reasonable adjustments at any time, please let us know by contacting us on reasonable.adjustments@bbc.co.uk. Job Introduction Partner Engineering is focused on getting BBC iPlayer, BBC Sounds and Connected Bridge for TV working on partner devices from major international manufacturers. We work closely … it is rewarding. Every tick of the clock, our content reaches millions of people globally, which is made possible by our top-notch Software Engineering team. They've been instrumental in pioneering innovative products and unique features that have firmly positioned us at the forefront of our industry. We more »

such as natural language processing, computer vision, doc intelligence etc Experience in working with large and complex datasets, data pipelines, data pre-processing, and feature engineering Experience in designing and architecting solutions Experience in cloud computing, distributed systems, microservices, and APIs Experience around productionising AI/ML models … Excellent communication, collaboration, and problem-solving skills Desirable: Prompt engineering Lang Chain/Semantic Kernel Frameworks Experience exploring, analysing, and visualising data Additional Information Location: This role can be delivered in a hybrid nature from one of these offices Belfast, Birmingham, Manchester, Edinburgh, London or Newcastle upon Tyne. At more »

statistics, and data structures within relevant technical projects. Proficiency in programming languages, frameworks, and tools, such as Python, TensorFlow, PyTorch. Experience with data preprocessing, feature engineering, and model evaluation techniques. Highly Desirable: Experience working on aerospace-related projects Experience deploying MLOps solutions and working within CI/CD 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 »

following areas: Statistics, Machine Learning, Deep Learning & AI You will have experience at each process within data science, problem definition, data acquisition & wrangling, modelling, feature engineering and deployment What’s equally relevant is programming knowledge and a gift for coding using: R, Python, SQL, SAS or Spark You more »

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 »

areas: Statistics, Machine Learning, Deep Learning & AI You will have significant experience at each process within data science, problem definition, data acquisition & wrangling, modelling, feature engineering and deployment What’s equally relevant is programming knowledge and a gift for coding using: R, Python, SQL, SAS or Spark You more »

in the modern day audit. You’ll get to work on technical assignments enabling you to develop skills in Advanced Analytics, Machine Learning, Data Engineering and sophisticated visualisation tools to provide clients with the PwC digital audit experience. This means that you’ll develop the technical, business and soft … Tableau) Understanding of common data quality issues and they effect they have on machine learning models; Data cleansing and manipulation for machine learning (e.g. feature engineering); Robotics experience eg UI Path; Experience and be able to demonstrate finance/accounting understanding; Experience with financial/general ledger data more »

in the modern day audit. You’ll get to work on technical assignments enabling you to develop skills in Advanced Analytics, Machine Learning, Data Engineering and sophisticated visualisation tools to provide clients with the PwC digital audit experience. This means that you’ll develop the technical, business and soft … Tableau) Understanding of common data quality issues and they effect they have on machine learning models; Data cleansing and manipulation for machine learning (e.g. feature engineering); Robotics experience eg UI Path; Experience and be able to demonstrate finance/accounting understanding; Experience with financial/general ledger data more »

Our data scientists will be a part of the Intelligent Systems based in London but will work closely and collaborate with global product and engineering teams across the globe. The Intelligent Systems team is at the forefront of driving innovation through cutting-edge data science, machine learning, and generative … quantifying business impact. Proficiency in Python programming. Expertise in GIT and the data science Python stack. Experience with real-world data querying, manipulation, and feature engineering. Familiarity with cloud technologies. Strong attention to detail and ability to work independently with given direction. Efficient time and task management skills. Entrepreneurial … mindset and a can-do attitude. Passion for software development and engineering. Ability to collaborate in interdisciplinary teams of product, engineering, business, and technology experts. Desired skills Excellent communication skills with the ability to effectively engage with diverse stakeholders. Experience in a consumer-oriented, product-focused, or eCommerce business. more »

reliability of our AI-driven applications. Key Responsibilities: Design, implement, and optimize ML workflows and pipelines on Google Cloud Platform (GCP), including data ingestion, feature engineering, model training, evaluation, and deployment. Collaborate with data scientists, machine learning engineers, and software developers to streamline ML model development and deployment … infrastructure. Implement version control, testing, and CI/CD pipelines for ML models and code. Requirements: Bachelor's degree or higher in Computer Science, Engineering, or related field. Proven experience as an ML Ops Engineer or similar role, with hands-on experience deploying and managing ML workflows in cloud more »

solution offerings. Provide expertise and guidance on AI best practices, contributing to the organization's AI strategy and innovation efforts. Conduct data analysis and feature engineering to prepare data for use in AI models, utilizing Azure Data Lake and other data storage solutions. Develop robust testing and validation … Service, Azure Cognitive Services, and Azure Machine Learning. Familiarity with Azure Databricks is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large datasets, experience with Azure more »

probabilistic cyber risk model for the (re)insurance and financial services markets. Define and implement a globally consistent best practice process for data validation, feature selection, and modeling of catastrophe exposures. Lead best practices to design and extend an agile and flexible modeling framework. Developing and implementing methodologies to … analytics point of contact and collaborate directly with clients and cli facing teams Collaborating with other leaders across the Analytics organization, including Product Management, Engineering, and Client Engagement Qualifications: MS degree in Applied Mathematics, Statistics, Engineering or similar quantitative disciplines Mastery of deep learning non/parametric models … and interpretability 5+ years of experience in catastrophe risk Modeling, Applied Statistics, Probability theory, Monte Carlo methods for uncertainty quantification and propagation, GLMs applications, feature engineering, data visualization, and hypotheses testing True passion for leading, inspiring, mentoring, and attracting world-class colleagues Experience working with different types of 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 »

Ability to analyse and manipulate large datasets Solid understanding of digital signal processing, specifically related to audio and music. Knowledge of data preprocessing and feature engineering techniques Experience with machine learning frameworks and libraries Ability to work independently and collaboratively in a remote setting A good working knowledge more »

Actions Implementing the machine learning life cycle: building models in a structured manner following best practice in the collection and analysis of modelling data, feature engineering, model fitting, selection, evaluation, deployment, and monitoring. Working independently and providing support and guidance to others. Receiving guidance from managers only in more »

projects on time and within scope. fundamentals in programming, statistics, mathematics, and ML algorithms (neural networks, tree-based methods, optimizers, super/unsupervised learning, feature engineering, etc.). Strong experience with Python required understanding of the ML/DS frameworks (XGBoost, Scikit-learn, Pandas, Numpy, etc.), and modular …/modern OOP software design practices with a modern ML/Data/Cloud engineering technical stack If you’re interested in this role and feel you fit some of the requirements, apply through the advert to find out more information. Senior Machine Learning Engineer 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 »

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 »