Top Data Jobs in London
The Market Data Specialist will improve and support the Security Master and Corporate Action Management systems, focusing on data quality, cleaning, validation, and resolving internal client support issues while interfacing with data providers.
The Data Engineer will analyze and manage data to support trading, focusing on understanding, cleaning, and sharing datasets. Responsibilities include automating ETL processes, checking for anomalies, and collaborating with traders and software engineers to generate insights.
The Data Science Lead will manage data science projects, enhance and monitor the digital twin model's accuracy, and collaborate with cross-functional teams to translate business needs into analytical solutions. The role involves guiding data strategy, developing performance metrics, and mentoring team members to foster innovation.
As a Data Scientist, you will analyze large data sets to identify opportunities for optimization and test the effectiveness of various actions. You will develop algorithms and data models, apply data mining techniques, and conduct statistical analyses to create high-quality predictive systems.
The Data Analytics role involves transforming data into insights to inform business decisions. Responsibilities include conducting lifecycle analysis, developing reporting capabilities, and monitoring performance for quality improvement.
As a Lead Price Comparison Data Analyst, you will analyze insurance price comparison data, transforming it into engaging insights for non-technical stakeholders. You will collaborate with various teams to optimize pricing models and present data findings to senior leadership, driving customer insights and business strategies.
As an Entry-Level AI Data Rater, you will evaluate e-commerce data, follow specific guidelines for research, and rate the usefulness of product filters. This role offers comprehensive training and is ideal for entry-level candidates eager to gain experience in AI technologies.
As a Senior Data Engineer, you'll design, build, and maintain data infrastructure, ensuring data pipeline reliability and efficiency. Collaborate with cross-functional teams, enhance data quality, implement automation, and manage data transformation workflows to deliver high-quality data solutions.
The SAP Data and Integration Analyst at Royal Canin will support the EOS business transformation by designing integrations for SAP S/4 related to the Make to Deliver template, focusing on master-data and transactional integrations. The role requires collaboration with various technical teams and creating interface specifications and test plans.
The Senior Data Engineer will lead the data engineering function, work on a modern data platform, and create data-as-product solutions. Responsibilities include assembling complex data sets, building ETL infrastructure, maintaining the Data Warehouse platform, and ensuring the platform adheres to financial models. The role requires strong leadership in coaching and mentoring along with effective communication skills.
The Data Engineer will develop databases and data pipelines, create end-to-end data solutions, and maintain scalable data solutions while collaborating with various stakeholders to ensure data security and project success.
The Senior Market Data Analyst will manage market data sourcing, transformations, and models while analyzing large datasets and enhancing reporting tools. Responsibilities include collaborating with teams to support market risk initiatives and ensuring high data quality standards. The candidate will also coordinate agile projects and resolve market data queries from stakeholders.
As a Senior Data Engineer at Notabene, you'll build and maintain scalable ETL pipelines, drive a data-driven culture, and collaborate with cross-functional teams to extract actionable insights from data. You'll promote data governance and security practices while ensuring the performance and scalability of data infrastructure.
The Senior Data Analyst will work closely with stakeholders to translate business requirements into data solutions, analyze large datasets for insights, validate data accuracy during migration, and ensure data quality. Responsibilities include collaborating with Data Engineers, creating data validation processes, providing ad-hoc analyses, and documenting methodologies.
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