Data Scientist

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: 

• Contribute to the development of an enterprise‑grade data management framework, including data acquisition, cleaning, transformation, and workflow optimization. 

• Help design and refine user experiences for financial analytics data pipelines, integrating multiple tools and services into coherent, efficient workflows. 

• Work closely with analytics domain experts to understand business data requirements and translate them into platform components, models, or analytical workflows. 

• Collaborate with engineering and project delivery teams to implement data solutions that align with product and organizational goals. 

• Support communication of project progress, insights, and outcomes to product, engineering, and business stakeholders. 

• Stay current with emerging technologies, modelling techniques, and market trends in financial analytics to inform continual improvement. 

• Build, train, test, and validate machine learning and deep learning models, including NLP, LLMs, and Retrieval‑Augmented Generation (RAG). 

• Develop evaluation frameworks and metrics to assess automation and AI solutions against business requirements. 

• Apply web scraping, crawling, entity extraction, and advanced pre‑/post‑processing techniques to prepare structured, semi‑structured, and unstructured data (including PDFs and scanned documents). 

• Build and deploy data and ML solutions on cloud platforms (AWS or similar), following MLOps and CI/CD best practices. 

Required Skills: 

• 3–5 years of experience in data science, analytics, or statistical modelling roles. 

• Solid grounding in data analytics, feature engineering, predictive modelling, NLP, LLMs, and RAG workflows. 

• Strong proficiency in Python and commonly used data science libraries (Pandas, NumPy, Scikit‑learn, etc.), with hands‑on model development experience. 

• Familiarity with deep learning frameworks such as TensorFlow or PyTorch. 

• Experience with Git and CI/CD pipelines (GitLab/GitHub runners). 

• Strong understanding of statistics, relational databases, and statistical programming concepts. 

• Ability to work effectively with large and complex datasets. 

• Understanding of MLOps practices and experience with cloud environments (AWS/Azure). 

• Experience with commercial or open‑source data management tools. 

• Strong analytical, problem‑solving, and prioritization skills. 

• Effective communication skills with the ability to clearly articulate technical and conceptual ideas to both technical and non‑technical audiences. 

• Ability to set and uphold coding standards. 

• Ability to collaborate across teams and contribute to strategy execution through strong technical insight. 

• Hands-on experience with leading commercial or open-source data management tools. 

• Ability to diagnose and resolve complex technical and business problems using deep analytical and industry knowledge 

• Broad business awareness and understanding of relevant internal business relationships. 

 

Preferred 

• Experience working in financial services or investment banking. 

• Familiarity with Refinitiv or LSEG datasets, tools, or workflows. 

• Experience working with distributed or cross‑location teams. 

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 Python, R, and SQL 

 

Career Stage:

Senior Associate

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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