At a Glance
- Tasks: Lead a team to build innovative AI solutions for financial markets.
- Company: Join a leading global financial markets infrastructure provider.
- Benefits: Flexible work, healthcare, retirement planning, and paid volunteering days.
- Other info: Collaborative culture that values diversity and continuous learning.
- Why this job: Shape the future of AI while making a real impact in finance.
- Qualifications: Proven leadership in AI/ML with strong technical expertise.
The predicted salary is between 63000 - 77000 £ per year.
Are you an experienced Data Science leader with a passion for building and scaling AI/ML products? Lead a team of exceptional Data Scientists and ML Engineers building next-generation AI solutions for financial markets. Drive innovation using LLMs, Generative AI, Deep Learning, Transformers, Agentic AI, and advanced Machine Learning to deliver real-world business impact. If you're passionate about shaping the future of AI, we'd love to talk to you.
ROLE SUMMARY
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. 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
- 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.
- Drive hiring, onboarding, succession planning, and team growth initiatives.
- 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.
WHAT YOU'LL BRING
ESSENTIAL SKILLS
- LEADERSHIP & MANAGEMENT
- 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.
- 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.
- 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.
WHAT YOU'LL GET IN RETURN
- HIGH-IMPACT AI LEADERSHIP
- Lead the development of next-generation AI products, demonstrating large-scale datasets, advanced AI models, and modern technologies to solve complex customer challenges.
- SIGNIFICANT OWNERSHIP
- Shape AI strategy, influence product direction, and build capabilities that deliver dynamic outcomes for customers worldwide.
- INDUSTRY LEADERSHIP
- Work at the forefront of Generative AI, LLMs, Agentic AI, Analytics, and Intelligent Search, helping define the future of AI innovation in financial markets.
- CAREER GROWTH
- Accelerate your leadership and technical career through continuous learning, innovation, and exposure to large-scale AI initiatives.
WE ARE PROUD OF OUR VALUES
We recognize that attracting exceptional talent requires flexibility and inclusivity. We take a hybrid-first approach and are committed to creating an environment where different perspectives, continuous learning, and innovation can thrive.
Join us and be part of a team that values innovation, quality, and continuous improvement. LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth. Our purpose is the foundation on which our culture is built. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.
Data Science Manager (REMOTE) employer: London Stock Exchange Group
At London Stock Exchange Group, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Lead Java Engineer in our Risk Platform team, you will have access to unparalleled growth opportunities, working alongside industry experts in a vibrant London setting that champions diversity and professional development. Join us to make a meaningful impact while enjoying competitive benefits and a supportive environment that values your contributions.
Contact Details:
London Stock Exchange Group Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Manager (REMOTE)
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We think you need these skills to ace Data Science Manager (REMOTE)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
