1,026 to 1,050 of 1,876 Use Case Jobs in England

ambitious revenue and growth targets and move quickly to capture market opportunity. Lead the go‐to‐market - Define priority audiences, regions and use cases. Partner with Product, Pricing and Operations to ensure strong product‐market fit and a compelling, localised proposition. Champion the French customer - Be the voice ...

strong understanding of our internal AI tool stack. From there, you’ll act as a trusted advisor—guiding teams on which tools to use for specific use cases, especially when it comes to process automation and intelligent solutions. The role is not just about knowing … when a conditional job offer is made. A conviction does not automatically lead to withdrawal of the offer: we make decisions on a case-by-case basis and take a number of relevant factors into account (e.g. the role you are applying for and the circumstances ...

insight back into the business. What you’ll do Deliver engaging, tailored Plan-Apps MMP demonstrations that respond to each audience, use case and stage of the customer journey. Lead discovery workshops alongside the Change Lead, uncovering customer priorities and translating them into relevant platform use ...

pipelines for auction, inventory, customer, and transaction data.• Develop reusable transformation models and curated datasets in Snowflake and dbt for analytics and operational use cases.• Orchestrate complex dependencies with Airflow, Dagster, or a comparable workflow platform.• Design data models and interfaces that are clear, scalable, and easy … regulated data environments.How success will be measured• Critical pipelines and datasets are reliable, observable, and trusted by their users.• Teams can find and use well-documented data products without unnecessary handoffs.• New analytics and ML use cases move from idea to production faster because the underlying ...

sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well‐governed and high‐performing data use across the firm. At Goldman Sachs, engineering teams shape scalable systems, solve complex technical problems and turn data into action. In data engineering roles … within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision‐making and emerging AI use cases. Role Summary As a Data Engineer, Lakehouse and AI Data Platform , you will design, build, test and support data pipelines and curated datasets ...

maturity assessments. Define the high-level target data architecture, technology stack and governance framework. Contribute to data ontology design for AI/analytics use cases and the overall data strategy roadmap. Present findings and recommendations to senior client stakeholders and support stakeholder sign-off. Use Python ...

foundations that make the platform and its Data Products easier to understand, discover, trust, and consume for both traditional analytics and AI-enabled use cases (for example, strengthening semantic consistency, metadata and lineage, data quality signals, and modern consumption patterns) Job responsibilities Provides technical guidance and direction … ready (e.g., consistent meaning and definitions, strong metadata/lineage and quality signals, and consumption patterns that support both analytics and AI-enabled use cases). Drives decisions influencing product design, data product contracts, distribution approaches, and engineering processes to improve time-to-data, reliability, and consumer experience ...

programme, not just in theory ML and AI platform work: feature stores, MLflow, model serving, and the data foundations behind RAG or agentic use cases Regulated-sector exposure financial services, healthcare, public sector and the assurance that comes with it How you work Opinionated but not dogmatic: recommends … says so when a client's preferred tool is the wrong one Comfortable being the only data person in the room and building the case from scratch Writes clearly decision records, options papers and diagrams a client executive can act on Commercially aware: understands utilisation, margin ...

drive measurable value and shape the future of AI adoption in life sciences. Responsibilities Design and implement AI-driven solutions across life sciences use cases such as drug discovery, clinical trial optimization and pharmacovigilance Advise executive stakeholders on AI strategy and translate technical concepts into actionable business outcomes … business teams to tailor solutions to client needs Deploy AI and machine learning models in production environments using established MLOps and LLMOps practices Use cloud platforms and data solutions to ensure scalability and operational integrity Present data-driven recommendations to senior audiences, demonstrating the impact of AI solutions ...

agentic workflow components. Design, build, integrate, deploy, and operate production AI/ML and LLM-based services for legal research, analytics, and content use cases. Implement RAG, semantic search, embeddings‐based retrieval, ranking, summarisation, classification, content enrichment, and citation‐aware AI capabilities where appropriate. Design and implement agentic … Desirable experience with event‐driven architecture, messaging, queues, asynchronous processing, retries, idempotency, and failure handling. Desirable experience with legal content systems, LegalTech, publishing platforms, case law, citation systems, legal research workflows, XML/XSLT, structured content processing, search, ranking, indexing pipelines, or content enrichment. Why Join Us? Join ...

Описание EPAM helps pharmaceutical and life sciences organizations use data, AI, and advanced analytics to transform R&D, clinical, and commercial functions. Its solutions address drug discovery, clinical development, pharmacovigilance, and patient engagement. Задачи Design and implement AI-driven solutions for drug discovery, clinical trial optimization, and pharmacovigilance … clinicians, and business teams to tailor solutions to client needs; Deploy AI and machine learning models in production using MLOps and LLMOps practices; Use cloud platforms and data solutions to ensure scalability and operational integrity; Present data-driven recommendations to senior audiences and demonstrate the impact ...

Work directly with client stakeholders to understand business requirements and translate them into scalable data and AI solutions. Support AI and Generative AI use cases using Oracle AI Services, OCI Generative AI, Vector Search and Oracle Database 23ai (or above) capabilities. Guide development teams and provide hands … managing discrete client engagement Ability to build and maintain relationships with clients. Multiple lifecycle implementations of Oracle AI solutions, including the following phases: business case, requirements gathering, fit/gap analysis, Cloud architecture, design documentation, and deployment. Set Yourself Apart: Confidence in presenting challenging points of view to client ...

Work directly with client stakeholders to understand business requirements and translate them into scalable data and AI solutions. Support AI and Generative AI use cases using Oracle AI Services, OCI Generative AI, Vector Search and Oracle Database 23ai (or above) capabilities. Guide development teams and provide hands … managing discrete client engagement Ability to build and maintain relationships with clients. Multiple lifecycle implementations of Oracle AI solutions, including the following phases: business case, requirements gathering, fit/gap analysis, Cloud architecture, design documentation, and deployment. Set Yourself Apart: Confidence in presenting challenging points of view to client ...

agentic AI. This role combines deep supply chain domain expertise with a practical understanding of digital and AI capabilities to identify high-value use cases, shape transformation roadmaps and support delivery of scalable solutions across planning, procurement, manufacturing, logistics, inventory, fulfilment and customer service.What You'll Be DoingPartner … optimization, and service operations.Evaluate and build business cases by assessing business value, data readiness, process maturity, technology fit, and implementation feasibility for AI use cases.Design AI transformation roadmaps and solutions by translating business requirements into actionable plans and supporting the implementation of AI, Machine Learning, Generative ...

solutions Manage customer engagements from discovery and requirements gathering through technical onboarding, training, feedback collection and completion Conduct workflow assessments to identify customer use cases, business requirements and opportunities for artificial intelligence-enabled improvements Support customers with solution configuration, access, entitlements, application programming interface integrations and technical setup … documentation Provide best-practice and consultative guidance to support stable deployments and effective solution adoption Partner with prospective and existing customers to validate use cases and support strategic commercial opportunities Collaborate with client technical teams and internal subject-matter experts to investigate and resolve product, data, access ...

lifecycle management Develop innovative machine learning solutions, including generative AI and multi‐agent approaches, and define evaluation, safety, and monitoring strategies for production use Own production deployment patterns including containerization, continuous integration and delivery, automated testing, model and prompt registries, model and version governance, monitoring and alerting … influence roadmaps, align on requirements, and deliver data‐led transformations Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management Provide technical leadership and mentorship through code reviews ...

pipeline development. Experience in building scalable and resilient data platforms in the public cloud. Data modelling and wrangling expertise to support advanced analytical use cases and ML, AI opportunities. Experience with containerisation technologies ( Docker, Kubernetes ) for scalable data solutions. Experience with vector databases and graph databases (e.g., Pinecone … data integrations acrossETL and streaming services ( Glue, MSK, Kinesis, Kafka ) Familiarity with AI developer tools like Cursor and GitHub Copilot and desire to use them to 10x your throughput. Collaborative approach and excellent communication skills. Strong problem-solving abilities and creative thinking, with critical thinking credentials to solve ...

lifecycle management Develop innovative machine learning solutions, including generative AI and multi-agent approaches, and define evaluation, safety, and monitoring strategies for production use Own production deployment patterns including containerization, continuous integration and delivery, automated testing, model and prompt registries, model and version governance, monitoring and alerting … influence roadmaps, align on requirements, and deliver data-led transformations Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management Provide technical leadership and mentorship through code reviews ...

analytics, reporting, and AI/ML consumers Design feature stores and data pipelines that support AI/ML model training and inference for use cases such as FX pricing, payment anomaly detection, and limit utilisation forecasting Evaluate and integrate AI‐assisted data tooling (AI‐powered cataloguing, natural language … have direct experience with the majority of these platforms and the ability to define coherent architecture across heterogeneous stores: Platform/Store Primary Use Snowflake Enterprise data warehouse, analytics, reporting, data sharing Oracle DB Migration strategy, data contracts, schema versioning Redis Cache invalidation, persistence strategy, data consistency MongoDB ...

continuously evolving our recruitment processes to ensure fairness and are open to accommodating any needs you might have. AI Disclosure: We use AI tools ("Google Gemini") to help our team source and review applications for roles with a high volume of applications. These tools assist our recruiters … foundational machine learning models and infrastructure, such as product matching models, image embedding services, and lightweight classifiers, that support multiple product and marketing use cases across Depop. As a staff-level member of the team, you will be expected to set the technical vision, lead high-impact initiatives ...

Discovery & Co-creation: Lead intensive discovery phases, collaborating closely with internal Investor Services clients, product, operations, and engineering teams to uncover needs, define use cases, and co-create rapid prototypes. Facilitate workshops and design sprints to refine concepts and gather feedback. Forward Engineering & Prototyping: Drive a forward-engineering … protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi's EEO Policy Statement and the Know ...

efficient and reliable. AI is central to how we work at Zego, and that extends to engineering. You'll be encouraged to use AI tools to move faster, automate the routine, and focus your time on the problems that matter most, while staying thoughtful about where … streaming systems within our existing architecture. Ensure data is modelled and structured to meet the needs of analytics, data science, and operational use cases. Contribute to improvements in our data systems and tooling. Collaboration & Delivery Work with teams across the business to understand requirements and turn them into ...

will be a senior hands-on engineer and technical leader responsible for building and operating scalable data and analytics services supporting Markets risk use cases. You will lead delivery across ingestion, transformation, storage, and consumption layers, with a strong focus on operational excellence and predictable outcomes. You will … data modeling, partitioning, and performance tuning strategies for large datasets. Build reusable frameworks and components to accelerate onboarding of new datasets and analytics use cases. Engineer data products and workflows spanning Databricks and Amazon Redshift, including ingestion patterns, transformations, and serving layers. Define approaches to reconciliation, consistency, lineage ...

strong engineering practices across source control, CI/CD, testing,documentation,monitoringand error handling. Develop andmaintaindata models to support reporting,analyticsand wider business use cases. Collaborate with other Data Engineers and technical teams to improve data architecture, platformperformanceand engineering processes. Work closely with Reporting, Insights and Data Science … resilience and consistency across the data estate. Why PHMG Tech? The IT, Development and Data functions within PHMG continue to evolve how we use technology and data to deliver value to the business. We want to build an open, collaborative culture where people communicate honestly, support each other ...

secure data pipelines, warehouses, and streaming systems. Ensure data is modelled and structured to meet the needs of analytics, data science, and operational use cases. Contribute to the evolution of our data architecture, ensuring it can support both current and future business needs. Collaboration & Delivery Partner with teams … engineers through code reviews, pairing, and knowledge sharing. Pragmatic approach to balancing technical excellence with delivery needs. You work AI-first. You will use AI daily here, and we mean daily. You do not need to arrive an expert, but you do need to arrive curious, experiment fast ...