# Emerging Tech Standard Delivery Team Member **Company**: London Stock Exchange Group (LSEG) **Location**: London **Experience**: senior **Job type**: full-time **Category**: Data Science **Industry**: Finance **Apply**: https://lseg.wd3.myworkdayjobs.com/en-US/Careers/job/IND-Bangalore-TowerERMZ-Infin/Lead-Data-Scientist_R0121304-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_3a0216a1-772 ## Description The Emerging Tech Standard Delivery Team drives the adoption of advanced technologies and develops enterprise-ready solutions for D&A Operations. You will partner with Operations and Technology teams to design data-driven solutions that deliver clear business and customer value. **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 a data science perspective, removing obstacles and taking ownership to find creative solutions. - Serve as a technical authority upholding best practice, and architectural recommendations. **Business & Stakeholder Engagement** - Partner with domain experts and senior business stakeholders 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 cross-functional teams by providing clear, data-driven recommendations and technical direction. **Advanced AI/ML Delivery & Emerging Technologies** - Design, build, and optimize production-grade AI models,including deep learning, NLP, large language models, and Retrieval-Augmented Generation (RAG). - Demonstrate strong expertise with LLMOps and advanced MLOps frameworks, including vector databases, orchestration tools (e.g., LangChain, LlamaIndex), and scalable model-serving platforms to manage end-to-end LLM lifecycle. - Assess third-party AI technologies, frameworks, and tools to inform build-versus-buy decisions and strengthen platform capabilities. - Establish and uphold high coding standards, reproducibility practices, and quality controls for robust ML development. **Data Engineering & Processing Expertise** - Apply strong expertise 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 modern MLOps workflows, CI/CD pipelines, and cloud-native deployment practices. - Lead scalable deployment of ML/AI solutions on AWS, Azure, or equivalent cloud environments. - Partner with platform engineering to enhance monitoring, observability, and full model lifecycle management. **Continuous Improvement & Innovation** - Stay abreast of emerging trends in AI, NLP, cloud computing, financial analytics, and ML engineering. - Champion experimentation, innovation, and adoption of frontier techniques and tools. - Identify opportunities to mature frameworks, modelling practices, and engineering processes across the organization. **Required Skills** - 8-12 years of experience in data science/AI with strong ownership of complex initiatives. - Own end-to-end AI/ML lifecycle: problem definition, design, experimentation, deployment, and continuous improvement. - Drive technical strategy: select models, define metrics, and balance trade-offs (performance, scalability, cost). - Lead development of advanced AI solutions: LLMs, GenAI, multimodal systems, and RAG workflows. - Ensure production-grade delivery: partner with Engineering for secure, scalable, and reliable deployments (MLOps/LLMOps, CI/CD). - Define and sign off success criteria: evaluation frameworks, quality thresholds, and production readiness. - Ensure Responsible AI & compliance: governance, explainability, documentation, and audit readiness. - Act as technical authority: resolve risks, guide and mentor data scientists and ML engineers. - Translate business needs into scalable AI solutions and influence cross-functional stakeholders. - Demonstrate deep hands-on expertise in Python, ML/DL frameworks, NLP, LLMs, and RAG. - Strong experience in MLOps/LLMOps, production deployment, and Git-based CI/CD workflows. - Solid foundation in statistics, data engineering, and large-scale data processing. - Proficiency in cloud platforms (Azure/AWS) and modern data ecosystems. - Experience with AI agents, human-in-the-loop systems, and synthetic data techniques. - Strong problem-solving, strategic thinking, and communication skills. ## Skills ### Required - Python - ML/DL frameworks - NLP - LLMs - RAG - MLOps/LLMOps - CI/CD workflows - cloud platforms - data engineering - large-scale data processing - statistics ### Nice to have - investment banking or financial services - enterprise AI governance - risk frameworks - regulatory compliance programs - research publications - patents - conference presentations in AI/ML/NLP --- Source: [Apply at lseg.wd3.myworkdayjobs.com](https://lseg.wd3.myworkdayjobs.com/en-US/Careers/job/IND-Bangalore-TowerERMZ-Infin/Lead-Data-Scientist_R0121304-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)