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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Science Manager - **Company:** London Construction Jobs - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Artificial Neural Networks, Automated Storage and Retrieval Systems, Microsoft Azure, Cloud Engineering, Continuous Integration, DevOps, Distributed Systems, Graph Database, Python (Programming Language), Machine Learning, Open Source Technology, Tensorflow, Azure Machine Learning, Software Safety, Search Technologies, Software Deployment, Reinforcement Learning, Pytorch, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Model Validation, Generative AI, Containerization, AI Platforms, Scikit Learn, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Optimization Algorithms, HuggingFace, Machine Learning Operations, Virtual Agents, Software Coding, GPT, Data Pipelines, Data Generation - **Published:** September 24, 2026 - **Apply:** https://www.totaljobs.com/job/data-science-manager/london-stock-exchange-job108031719 ## About the Role Are you an experienced Data Science leader with a passion for building and scaling AI/ML products?, * Proven track record of building, leading, and developing high-performing teams of Data Scientists, ML Engineers, and AI practitioners. * Demonstrated success delivering large-scale AI initiatives from ideation to production with measurable business impact. * Strong coaching, mentoring, performance management, and talent development capabilities. * Experience leading multiple concurrent programs, balancing priorities, resources, and customer expectations. * Exceptional leadership, communication, and influencing skills with experience engaging senior leadership and executive collaborators. TECHNICAL EXPERTISE * Extensive experience designing, building, and deploying production-grade AI and Machine Learning solutions at scale. * Deep expertise in LLMs, Generative AI, RAG, Agentic AI, Deep Learning, Neural Networks, and Transformer architectures. * Hands-on experience with LLM evaluation, benchmark design, model validation, prompt engineering, guardrails, and AI quality assessment. * Good foundation in statistics, probability, optimization, experimentation, and applied machine learning. * Advanced proficiency in Python and modern AI frameworks, including PyTorch, TensorFlow, Scikit-Learn, Hugging Face, LangChain, Semantic Kernel, and related ecosystems. * Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications serving thousands of users. * Strong understanding of model observability, monitoring, evaluation frameworks, experimentation, reliability, and operational perfection. * Expertise in cloud-native AI development using Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure AI Search, AWS AI Services, and modern cloud architectures. * Experience implementing MLOps and LLMOps practices, including CI/CD, model lifecycle management, governance, and production operations at scale. COLLABORATION & COMMUNICATION * Ability to communicate complex technical concepts clearly to technical, business, and executive audiences. * Strong interested party leadership skills with a proven track record to drive alignment across Product, Engineering, Research, and Business teams. * Known to work influencing technical strategy, product direction, and organizational decision-making. DESIRABLE SKILLS * Experience leading teams building AI products for financial services, capital markets, research, analytics, or other data-intensive domains. * Experience developing multi-agent systems, autonomous workflows, copilots, and intelligent AI assistants. * Knowledge of reinforcement learning, fine-tuning, synthetic data generation, model compression, and advanced optimization techniques. * Experience with Knowledge Graphs, vector databases, semantic search, retrieval systems, and Graph RAG architectures. * Strong understanding of Responsible AI, model governance, AI safety, privacy, regulatory compliance, and risk management frameworks. * Experience with DevOps, CI/CD, Kubernetes, Infrastructure as Code, containerization, and distributed computing platforms. * Contributions to the AI community through publications, patents, conference presentations, research, or open-source projects. EDUCATION Bachelor's degree or equivalent experience in Computer Science, Data Science, Statistics, Mathematics, Engineering, Physics, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's or equivalent experience or PhD preferred. ## Description As a Data Science Manager, you will lead a high-performing team of Data Scientists delivering AI-powered products that create measurable business value at scale. This role combines technical leadership, people leadership, and strategic execution. You will drive innovation in AI and Machine Learning, establish engineering excellence, and develop exceptional talent while delivering production-grade solutions that solve complex customer problems. The ideal candidate has a consistent track record of leading technical teams, scaling AI initiatives from concept to production, and fostering a culture of innovation, collaboration, and continuous improvement. You will partner closely with Product, Engineering, Research, and business partners to shape strategy, accelerate execution, and deliver impactful AI solutions. WHAT YOU'LL BE DOING This role combines technical leadership, organizational leadership, and strategic execution within a high-impact AI organization. Technical Leadership * Lead the design, development, evaluation, and deployment of production-grade AI and Machine Learning solutions. * Drive innovation in Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Deep Learning, and Transformer-based architectures. * Define the technical vision for AI products, ensuring solutions are scalable, secure, maintainable, and aligned with business objectives. * Provide deep expertise in model development, experimentation, optimization, evaluation, and production deployment. * Establish standard methodologies for LLM evaluation, model benchmarking, AI quality measurement, and performance assessment. * Evaluate emerging AI technologies, foundation models, and third-party solutions to find opportunities for innovation and business value. * Guide architectural decisions across AI platforms, model-serving infrastructure, data pipelines, and MLOps/LLMOps capabilities. * Partner closely with Engineering teams to productionize AI solutions and drive operational excellence. * Build, mentor, and lead high-performing teams of Data Scientists and AI/ML practitioners. * Set clear goals, drive accountability, and support career growth and development. * Lead performance management, coaching, feedback, and talent development activities. * Foster a culture of innovation, collaboration, ownership, and continuous learning. * Drive hiring, onboarding, succession planning, and team growth initiatives. * Accelerate technical excellence through mentoring, technical reviews, and knowledge sharing. Strategic & Delivery Leadership * Partner with Product, Engineering, and Business leaders to define AI strategy, roadmap, and priorities. * Drive execution through effective planning, prioritization, resource management, and delivery oversight. * Deliver high-quality AI solutions that create measurable business value. * Champion engineering excellence through guidelines, coding standards, experimentation, and governance. * Communicate technical strategy, risks, and recommendations clearly to technical and executive collaborators. * Promote responsible AI, model governance, compliance, and operational risk management., Shape AI strategy, influence product direction, and build capabilities that deliver dynamic outcomes for customers worldwide. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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