Scrum Lead

The Emerging Tech Standard Delivery Team drives the adoption of advanced technologies and develops enterprise level solutions for D&A Operations. In this role, the individual partners with Operations and Technology teams to design data driven solutions that deliver business and customer value.

The position requires expertise in data analytics, NLP, deep learning, and data communication, along with ability to learn financial content and core D&A business processes. The individual must know the latest technologies—including Generative AI, Multi-modal AI, LLMOps practices, AI Agents, and synthetic data techniques—and collaborate with operations groups and specialized machine‑learning teams to deliver scalable, innovative, and high‑impact solutions.

 

Role, Responsibilities & Key Accountabilities:

 

Strategic & Technical Skill

• Hands‑on technical expertise across end‑to‑end data science initiatives, ensuring high‑quality design, development, and delivery.
• Shape and refine the product vision for advanced data management and analytics frameworks spanning data acquisition, transformation, quality, and workflow automation.
• Define optimal user experiences for financial analytics pipelines, integrating diverse tools, datasets, and services into cohesive workflows.
• Own and drive large projects from data science perspective, removing obstacles and own creative solutions.
• Serves technical authority upholding standard, and architecture recommendations.

Business & Stakeholder Engagement

• Partner with domain SME and business owners to identify high‑value problems and co‑create AI/ML and platform strategies.
• Translate business requirements into technical specifications, solution designs, and measurable success criteria.
• Communicate complex insights, findings, and solution outcomes to product, engineering, sales, proposition, support, and leadership teams.
• Influence multi-functional teams by providing clear, data‑driven recommendations and technical direction.

Advanced AI/ML Delivery & Emerging Technologies

• Strategize, build, and optimize production‑grade AI models—including deep learning, NLP, large language models, and Retrieval‑Augmented Generation (RAG).
• Demonstrate expertise with LLMOps and advanced MLOps frameworks, including vector databases, orchestration tools (e.g., LangChain, LlamaIndex), and scalable model‑serving platforms to handle end‑to‑end LLM lifecycle
• Demonstrate strong expertise Generative AI and Multi-modal AI advancements, including models that handle text, images, audio, and video in unified architectures, significantly reducing pipeline complexity
• Assess third‑party AI technologies, frameworks, and tools to decide build‑versus‑buy decisions and strengthen platform capabilities.
• Establish and uphold high coding standards, reproducibility practices, and quality controls for robust ML development.
• Apply advanced model evaluation, tuning, scaling, and continuous improvement cycles.
• Apply AI Agent, human‑AI frameworks, adopt AI as a productivity amplifier across business functions
• Understanding Synthetic Data techniques to overcome real‑data scarcity, enhance model robustness, and support privacy‑preserving AI development

Data Engineering & Processing Expertise

• Apply strong skills in data extraction, including web scraping, crawling, entity recognition, and advanced pre/post‑processing.
• Work with complex structured, semi‑structured, and unstructured datasets—including financial documents, PDFs, and scanned content.
• Collaborate with data engineering teams to ensure scalable, reliable pipelines that support high‑impact analytics workflows.

Cloud, MLOps & Deployment Excellence

• Align with MLOps workflows, CI/CD pipelines, and cloud‑native deployment practices.
• Lead scalable deployment of ML/AI solutions on AWS, Azure, or any cloud environments.
• Partner with platform engineering to enhance monitoring, observability, and full model lifecycle management.

Continuous Improvement & Innovation

• Stay on top of emerging trends in AI, NLP, cloud computing, financial analytics, and ML engineering.
• Champion experimentation, innovation, and adoption of frontier techniques and tools.
• Find opportunities to mature frameworks, modelling practices, and engineering processes across the organization.

Team Development & Capability Building

• Mentor and support data scientists, enabling them to navigate complex challenges while elevating the organization’s talent pipeline and scientific excellence.
• Design, build, and onboard end‑to‑end solutions in close collaboration with Engineering and Operations teams.
• Define long‑term capability development roadmaps for the data science discipline—skills, tools, frameworks, and standards.
• Build the culture to innovate, with scientific complexity, and high engineering standards across the data organization.

 

Required Skills:

• 12+ years of experience in data science solutions, ML, AI research, or advanced analytics roles, including leadership of large and complex AI programs.
• Proved expertise architecting and scaling enterprise‑level AI systems and ML platforms.
• Deep knowledge of advanced ML domains—NLP, LLMs, RAG, generative AI, multimodal systems, and innovative model architectures.
• Strong ability to drive AI strategy, define long‑horizon technical roadmaps, and shape organization transformation through data and AI.
• Deep understanding of Generative AI & Multimodal AI architectures.
• Practical experience working with AI Agents and human‑AI frameworks.
• Knowledge of Synthetic Data generation techniques.
• Demonstrated track record of influencing senior executives and guiding multi-functional groups toward successful AI adoption.
• Technical mastery across Python, ML/DL frameworks (TensorFlow, PyTorch, Scikit‑learn), statistical methods, cloud platforms, and MLOps systems.
• Exceptional communication, storytelling, and thought leadership of guiding partners through complex concepts.
• Strong business understanding with the ability to translate frontier AI capabilities into relevant outcomes.

• Strategic business awareness and ability to influence different functional teams and resolve complex challenges.

 

Preferred

• Experience working within large investment banking or financial services organizations.
• Experience defining enterprise AI governance, ethics guidelines, risk frameworks, or regulatory compliance programs.
• Published research, patents, or conference presentations in AI, ML, NLP, or related fields.
• Experience working in multi‑team or matrixed delivery organizations across regions and time zones.
• Industry reputation as expert or AI leader with vision.

 

Education:

• Master’s degree or equivalent experience in Statistics, Mathematics, or Computer Science with a Data Science certification, or an Engineering degree specializing Data Science and Artificial Intelligence.
• Proficiency in programming languages such as Python, R, and SQL 

Career Stage:

Manager

London Stock Exchange Group (LSEG) Information:

Join us and be part of a team that values innovation, quality, and continuous improvement. If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.

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. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.

Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.

We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.

You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.

Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject.

If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.