Senior Data Scientist

Senior Data Scientist📍 Location: London, United Kingdom🏢 Industry: Information Services💼 Work Setting: HybridAre you passionate about advancing the future of AI-powered scientific discovery through large language models, retrieval systems, and intelligent research assistants?We are seeking a Senior Data Scientist I to join a centralized Platform Data Science organization focused on building the AI foundation behind scientific discovery and research platforms. This role will play a key part in developing next-generation AI experiences, including LLM-powered assistants, semantic search systems, agentic workflows, retrieval-augmented generation (RAG), and AI evaluation frameworks.The ideal candidate combines expertise in Generative AI, NLP, Information Retrieval, Machine Learning, Search Systems, and Applied AI Research with the ability to rapidly prototype and transform cutting-edge AI innovations into scalable production solutions.Key ResponsibilitiesApplied AI Research & DevelopmentDesign, prototype, and develop advanced AI solutions for scientific research workflows.Build intelligent systems that support:Scientific Question AnsweringLiterature SummarizationSemantic DiscoveryResearch Insight GenerationCitation-Aware ReasoningEvaluate and implement emerging AI techniques and architectures.Translate research concepts into scalable product capabilities.Drive innovation across AI-powered discovery experiences.Large Language Models (LLMs) & Generative AIDevelop and optimize LLM-powered applications.Design workflows utilizing:Foundation ModelsPrompt EngineeringContext ManagementGrounding StrategiesHallucination MitigationIntegrate LLMs with trusted scientific and scholarly content.Improve the accuracy, reliability, and trustworthiness of AI-generated outputs.Evaluate emerging model providers, architectures, and orchestration patterns.Agentic AI & Intelligent WorkflowsDesign and implement agent-based AI systems.Build multi-step reasoning workflows using tools such as:LangGraphLangChainWorkflow Orchestration FrameworksEnable intelligent decision-making and task execution capabilities.Improve automation of complex research and discovery processes.Develop reusable patterns for agentic AI applications.Search, Retrieval & Knowledge DiscoveryDesign and optimize enterprise-scale retrieval architectures.Develop:Lexical Search SystemsVector Search SolutionsHybrid Retrieval ArchitecturesImprove relevance and search effectiveness through advanced ranking methods.Support semantic exploration of scientific knowledge.Enable efficient discovery across large-scale research repositories.Retrieval-Augmented Generation (RAG)Build and enhance RAG pipelines that combine LLMs with scientific and biomedical content.Optimize:Embedding StrategiesRetrieval WorkflowsRe-Ranking ModelsChunking TechniquesContext Selection MethodsImprove answer quality, grounding, and factual accuracy.Support production deployment of AI-assisted research solutions.NLP & Semantic AIApply state-of-the-art techniques in:Natural Language ProcessingSemantic SearchEmbeddingsKnowledge RepresentationLanguage UnderstandingDevelop semantic enrichment solutions that improve content discoverability.Integrate metadata, ontologies, and domain knowledge into AI systems.Support knowledge-driven research and discovery experiences.AI Evaluation & ExperimentationDesign and maintain evaluation frameworks for search and AI systems.Measure performance using:NDCGRecallPrecisionGrounding MetricsFaithfulness MetricsHallucination DetectionBuild benchmark datasets and evaluation pipelines.Conduct offline and online experiments to assess model performance.Support A/B testing and continuous optimization initiatives.Responsible AI & Quality AssurancePromote responsible AI principles across product development.Evaluate:Model ReliabilityExplainabilityTrustworthinessAnswer AccuracyUser ImpactImplement strategies that improve transparency and safety.Support development of trusted AI research experiences.Production AI & Platform DevelopmentPartner with engineering teams to productionize AI and search capabilities.Develop scalable AI pipelines and workflows.Support deployment of production-ready AI systems.Contribute to platform architecture and long-term technical strategy.Ensure AI solutions are reliable, maintainable, and scalable.Cross-Functional LeadershipCollaborate closely with:Product ManagersSoftware EngineersUX ResearchersData ScientistsDomain ExpertsTranslate complex technical concepts into actionable business recommendations.Influence AI product roadmaps and strategic direction.Provide technical leadership across AI initiatives.QualificationsEducationRequiredMaster's Degree or PhD in:Computer ScienceData ScienceArtificial IntelligenceMachine LearningInformation RetrievalNatural Language ProcessingRelated Technical DisciplineExperienceRequiredSignificant experience in:Applied AIMachine LearningNLPInformation RetrievalGenerative AIExperience building production-grade AI systems.Experience developing search and retrieval solutions at scale.Experience translating research into production applications.Technical SkillsArtificial Intelligence & Machine LearningLarge Language Models (LLMs)Generative AIMachine LearningDeep LearningAI Reasoning SystemsRetrieval-Augmented Generation (RAG)NLP & SearchNatural Language Processing (NLP)Semantic SearchInformation RetrievalSearch RankingVector DatabasesEmbeddingsAgentic AILangGraphLangChainAgent WorkflowsAI Orchestration FrameworksMulti-Step Reasoning SystemsProgrammingPython (Advanced)Data Science LibrariesProduction AI DevelopmentAI & ML PlatformsDatabricksDistributed Computing PlatformsML Development EnvironmentsExperiment Tracking SystemsFrameworks & ToolsPyTorchHugging FaceLangGraphLangChainHaystackEvaluation & AnalyticsA/B TestingStatistical AnalysisEvaluation Framework DesignBenchmark DevelopmentExperimental DesignVisualizationTableauPower BIMatplotlibSeabornPreferred QualificationsExperience building:AI AssistantsConversational AI PlatformsAgentic AI SystemsExperience with:Recommendation EnginesSearch PlatformsRanking SystemsKnowledge of:Scientific Research ContentBiomedical DatasetsScholarly PublishingExperience with:Knowledge GraphsOntologiesSemantic Enrichment PlatformsExposure to:MLOpsProduction ML SystemsAI GovernancePublications or applied research in:NLPInformation RetrievalSearchGenerative AICore CompetenciesGenerative AILarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Information RetrievalSearch EngineeringAgentic AILangGraphLangChainNatural Language Processing (NLP)Semantic SearchAI EvaluationExperimentation & A/B TestingKnowledge GraphsMachine LearningPython DevelopmentDatabricksScientific AI ApplicationsApplied AI Research