51 to 54 of 54 Dimensional Modelling Jobs in the UK

The position requires at least 2 years of experience using QlikView version 11 or higher, with proven expertise in the following areas: Good knowledge of SQL, relational databases, and Dimensional Modeling Experience working with large data sets and complex data models involving more than 10 tables Integrating data from multiple sources into QlikView Data Models, including social media content … and API extensions Use of complex QlikView functions and developing optimal scripts for solutions Optimizing Dimensional data models for performance Primary Responsibilities: Creating and providing reporting and dashboard applications using QlikView and NPrinting to facilitate better decision-making Collaborating with stakeholders to gather requirements, and translating these into system and functional specifications Creating prototypes and conducting proof of concepts More ❯

we use to produce software. As the Lead Technical Architect (Data) , you will be responsible for defining Business and Analytics platform landscape for the future state. This will involve modelling and architecting data we use working alongside the Principal Enterprise Architect (Data). This role is responsible for transforming complex business structures, processes and activities into technical solutions with … analytics environment. Ownership and creation of data models that conform to existing and future standards and conventions. Collaborating and coordinating with multiple departments, stakeholders, partners, and external vendors. Data modelling - define the conceptual, logical and physical models for structures that will underpin operational and analytical systems. Guide project teams through the development process, ensuring that data is used effectively … be part of our Digital Transformation and join us on our journey to the cloud, while working closely with and sharing knowledge with the architecture function. Experience in Data Modelling: Proficiency in creating and managing data models, including conceptual, logical, and physical models. Experience in data platforms and/or data warehousing, defining architectures, designing pipelines and dimensional More ❯

together! The Role As a Senior Principal Data Scientist in the Multimodal Data & Analytics group you will be responsible for the discussion and implementation of data science and high-dimensional modeling methodologies applied to patient-level data (including various biomarker, clinical and outcomes data) across clinical development. You will combine your data science and AI skills and your scientific … identify opportunities for influencing internal decision making as well as discussions on white papers/regulatory policy. You will perform hands-on analysis of integrated clinical, outcomes and high-dimensional, patient-level biomarker data from clinical trials and the real world (genomics, transcriptomics, proteomics, flow cytometry etc.) to generate fit-for-purpose evidence that is applied to decision making … selection methods (e.g., lasso, elastic net, random forest), design of clinical trials. Familiarity with statistical and analytical methods for genetics and -omics data analysis and working knowledge of high dimensional biomarker platforms (e.g., next generation sequencing, transcriptomics, proteomics, flow cytometry, etc.). Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. More ❯

together! The Role As a Senior Principal Data Scientist in the Multimodal Data & Analytics group you will be responsible for the discussion and implementation of data science and high-dimensional modeling methodologies applied to patient-level data (including various biomarker, clinical and outcomes data) across clinical development. You will combine your data science and AI skills and your scientific … identify opportunities for influencing internal decision making as well as discussions on white papers/regulatory policy. You will perform hands-on analysis of integrated clinical, outcomes and high-dimensional, patient-level biomarker data from clinical trials and the real world (genomics, transcriptomics, proteomics, flow cytometry etc.) to generate fit-for-purpose evidence that is applied to decision making … selection methods (e.g., lasso, elastic net, random forest), design of clinical trials. Familiarity with statistical and analytical methods for genetics and -omics data analysis and working knowledge of high dimensional biomarker platforms (e.g., next generation sequencing, transcriptomics, proteomics, flow cytometry, etc.). Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. More ❯