The Emerging Tech Standard Delivery Team drives the adoption of advanced technologies and develops enterprise‑ready solutions for D&A Operations. In this role, the individual partners with Operations and Technology teams to design data‑driven solutions that deliver clear business and customer value.
The position requires strong expertise in data analytics, NLP, deep learning, and data communication, along with the ability to learn financial content and core D&A business processes. The individual must stay current with emerging technologies and collaborate closely with operations groups and specialized machine learning teams to deliver scalable, high‑impact solutions.
Role, Responsibilities & Key Accountabilities:
Strategic & Technical Leadership
- Lead, mentor, and develop a team of senior data scientists, providing technical direction, coaching, and performance feedback.
- Drive end‑to‑end delivery of data science initiatives, offering hands‑on technical leadership, removing roadblocks, and ensuring high‑quality execution.
- Own and refine the product vision for an advanced data management and analytics framework, covering data acquisition, transformation, quality, and workflow automation.
- Define and optimize user experiences for financial analytics data pipelines, integrating multiple tools, data sources, and services into cohesive workflows.
Business & Stakeholder Engagement
- Partner with domain experts and senior business stakeholders to identify high‑value problems and shape actionable AI, ML, and platform strategies.
- Translate business needs into technical specifications, solution designs, and clear success metrics.
- Communicate project goals, insights, and outcomes to product, engineering, sales, proposition, support, and leadership stakeholders.
- Influence cross‑functional alignment by providing clear, data‑driven recommendations and technical guidance.
Advanced AI/ML Delivery
- Develop, deploy, and optimize production‑grade AI models including deep learning, NLP, LLMs, and Retrieval‑Augmented Generation (RAG).
- Evaluate third‑party AI technologies, frameworks, and tools to guide build‑vs‑buy decisions that enhance platform capabilities.
- Establish and enforce coding standards, quality controls, and reproducibility practices for robust ML development.
- Lead model performance tuning, scalability improvements, and continuous enhancement cycles.
Data Engineering & Processing Expertise
- Apply deep expertise in data extraction techniques, including web scraping, crawling, entity recognition, and advanced pre‑/post‑processing.
- Manage complex structured, semi‑structured, and unstructured data—including financial documents, PDFs, and scanned inputs.
- Collaborate with data engineering teams to ensure scalable and reliable data pipelines that support high‑impact analytical workflows.
Cloud, MLOps & Deployment Leadership
- Ensure strong alignment with MLOps workflows, CI/CD pipelines, and cloud‑native deployment practices.
- Lead scalable deployment of AI/ML solutions on AWS, Azure, or equivalent cloud environments.
- Work closely with platform engineering teams to enhance monitoring, observability, and model lifecycle management.
Continuous Improvement & Innovation
- Stay current with emerging technologies and trends in financial analytics, AI, NLP, cloud computing, and model engineering.
- Promote a culture of innovation by encouraging experimentation, exploration of frontier techniques, and continuous skill development across the team.
- Identify opportunities to improve frameworks, modeling practices, tools, and processes across the data science organization.
Required Skills:
- 8–12 years of experience in data science or related analytics and statistical modelling roles.
- Own and drive end‑to‑end AI/ML solutions—from problem definition and experimentation to production deployment and continuous optimization
- Define and lead technical strategy, including model selection, evaluation metrics, and trade‑offs across performance, scalability, and constraints
- Design and deliver advanced AI solutions (including NLP, LLMs, GenAI, and RAG) aligned with business outcomes
- Act as the primary technical authority, guiding data scientists and ML engineers while proactively identifying and resolving risks
- Establish and sign off on success criteria, including model evaluation metrics, quality benchmarks, and production readiness standards
- Ensure Responsible AI compliance, including governance, explainability, documentation, and audit readiness
- Collaborate with engineering teams to enable secure, scalable, and reliable production deployments using MLOps and CI/CD best practices
- Lead and mentor senior data scientists, driving full‑stack data science delivery and fostering strong problem‑solving and algorithmic thinking
- Apply deep technical expertise in Python, ML/DL frameworks (TensorFlow, PyTorch, Scikit‑learn), and large‑scale data processing
- Leverage strong foundations in statistics, data engineering, and cloud platforms (Azure/AWS) for production-grade solutions
- Translate business requirements into technical solutions and influence cross‑functional stakeholders to drive strategic outcomes
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 leading multi‑team or matrixed delivery organizations across regions and time zones.
- Industry reputation as a technical expert or AI thought leader.
Education:
- Master’s degree in Statistics, Mathematics, or Computer Science with a Data Science certification, or an Engineering degree specializing in 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.
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