As a Enterprise Data Scientist, you will leverage cutting-edge technologies and methodologies to deliver data-driven insights and solutions for complex customer needs. You will work on end-to-end solutions, including building Proof of Concepts (POCs) and production-grade agentic AI systems, professional services, and integrating third-party technologies with client systems. This role is pivotal to ensuring the successful implementation of data science-driven products and capabilities, with a key focus on AI, machine learning, generative AI, and Natural Language Processing (NLP). You will collaborate closely with cross-functional teams, delivering innovative solutions to customers in highly dynamic, data-intensive environments.
Role & Responsibilities:
- Lead and execute complex customer engagements across the Asia-Pacific region, utilizing specialized expertise in AI, Machine Learning, Generative AI, and NLP, including building POCs, agentic AI workflows, integrations, and deployments with customer workflows.
- Apply a combination of technical, product, and data science expertise to co-create solutions that address specific customer needs, including ideation, clarification, technical design, and documentation.
- Lead detailed customer presentations for complex technical propositions, focusing on explaining advanced data science concepts and AI/ML solutions in an accessible way.
- Manage relationships with internal and external stakeholders, ensuring that project and customer-specific technical requirements are captured, refined, and translated into actionable solutions.
- Oversee and contribute to the development of Proof of Concepts, ensuring integration with customer workflows and systems.
- Lead the technical design and implementation of AI and machine learning solutions that integrate with existing client infrastructure.
- Drive the adoption of advanced data science and AI technologies to deliver high-value solutions.
- Develop and present strategies for scaling AI solutions, utilizing cloud platforms (Azure, AWS, GCP) for production-ready deployments.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines and agentic AI systems that orchestrate multiple tools and models to solve customer problems.
- Establish LLMOps practices, including evaluation, guardrails, and observability, to ensure safe, reliable, and responsible deployment of generative AI solutions in line with regulatory expectations.
- Lead and mentor junior team members across the Singapore and broader Asia-Pacific team, fostering a collaborative environment for continuous learning and technical growth.
Qualifications and Experience:
- 10+ years of experience in data science or a related field, with a focus on AI, machine learning, and NLP, preferably in a senior technical or leadership role.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. A Ph.D. in a relevant field is a plus.
- Expertise in Natural Language Processing (NLP) and Generative AI with a deep understanding of the latest LLM landscape, including transformer-based architectures such as BERT and T5, and current frontier and open-weight models (e.g., GPT-5.x, Claude 4/5, Gemini 2.x/3.x, Llama 4, DeepSeek, Qwen) that are driving the evolution of NLP and agentic AI applications.
- Hands-on experience building agentic AI systems, including multi-agent orchestration (e.g., LangGraph, AutoGen, CrewAI), tool/function calling, and integration via the Model Context Protocol (MCP).
- Practical experience with Retrieval-Augmented Generation (RAG), including chunking strategies, embedding models, hybrid search, and retrieval evaluation.
- Experience fine-tuning and adapting large models efficiently, using techniques such as LoRA/QLoRA, parameter-efficient fine-tuning (PEFT), quantization, and distillation, along with LLMOps practices for prompt evaluation, guardrails, hallucination testing, and observability (e.g., LangSmith, RAGAS, Arize).
- Awareness of responsible AI and governance requirements, including model risk management and emerging regulation (e.g., EU AI Act) as applicable to financial services.
- Extensive experience with advanced machine learning and deep learning frameworks such as PyTorch, TensorFlow, Hugging Face, and JAX for NLP, multimodal (vision-language), and other advanced AI tasks.
- Deep knowledge of cloud services (AWS, GCP, Azure) and their use in data science workflows, particularly for deploying machine learning models at scale.
- Expertise in Python, with advanced knowledge of modern data science and machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, spaCy, as well as cutting-edge NLP frameworks like Hugging Face Transformers, Datasets, and NLTK for efficient model training, fine-tuning, and data preprocessing.
- Strong programming skills in Python, R, and SQL, with advanced proficiency in handling large-scale data using distributed data systems like Apache Spark, cloud-native NoSQL databases such as MongoDB, Cassandra, and DynamoDB, as well as search engines like Elasticsearch and vector databases for semantic search (e.g., Pinecone, Weaviate).
- Hands-on experience with data ingestion, data wrangling, and data pipeline orchestration using tools like Apache Kafka, Apache Spark, Airflow, and distributed computing frameworks like Dask and Ray.
- Experience with advanced data science methodologies, including ensemble learning, deep reinforcement learning, transfer learning, and deploying large pre-trained models for real-time inference and production.
- Ability to design, prototype, and deploy NLP models for a range of applications, from information retrieval to sentiment analysis, chatbots, and question answering systems.
- Demonstrated success in delivering solutions in complex, fast-paced environments with a focus on customer satisfaction and technical excellence.
- Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Proven experience in customer-facing roles is highly valued, particularly in the enterprise tech or financial sectors, ideally serving customers across Asia-Pacific.
- Familiarity with AI-powered product development in industries such as finance, healthcare, or e-commerce.
- Experience with data visualization tools like Tableau, Power BI, or Plotly to present data science findings effectively.
- Knowledge of regulatory requirements in finance, including experience working with financial data feeds and APIs; familiarity with the Singapore regulatory environment (e.g., MAS) is a plus.
Equal Employment Opportunity:
As a global business, we embrace diversity of culture, background, and thought, recognizing it as a key to our success. We are an Equal Employment Opportunity Employer and offer a drug-free workplace.
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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