The Commodities Content team collects, manages, and supplies content of various asset classes like Metals, Oils, Agriculture, Power, Gas, Coal & Carbon. 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:

Own the product vision for an industry‑leading data management framework, covering data acquisition, cleaning, transformation, and related workflows.
Support Lead Data Scientist on end-to-end AI/ML lifecycle: problem definition, design, experimentation, deployment, and continuous improvement.
Define an optimized user experience for financial analytics data pipelines, unifying multiple tools and services into an integrated workflow.
Partner with analytics domain experts to understand business data needs and translate them into a practical platform and framework strategy.
Lead the execution of this strategy in close collaboration with engineering and project delivery teams.
Communicate product goals, progress, and achievements to product, engineering, business leaders, sales, proposition, support, and other internal teams..
Stay informed on financial analytics market trends to maintain a forward‑looking, future‑ready strategy.
Continuously learn and adapt to emerging tech and techniques in financial analytics.
Develop and deploy production‑grade AI models and data‑driven solutions aligned with strategic objectives.
Tune and optimize AI models to improve accuracy, performance, and scalability.
Evaluate third‑party AI capabilities using both functional and non‑functional criteria.
Establish and enforce coding standards to ensure a maintainable, robust codebase.
Collaborate with Software Engineers and cross‑functional teams to define requirements, set direction, and shape development roadmaps.
Hands‑on experience in data science, including Natural Language Processing, Large Language Models, prompt engineering, and Retrieval‑Augmented Generation (RAG).
Skilled in training, testing, and validating deep learning models as well as classical machine learning models.
Ability to design and implement evaluation frameworks for automation solutions based on business requirements.
Experience building solutions and onboarding workloads on AWS or other cloud platforms.
Expertise in web crawling and scraping techniques, entity identification and extraction, and advanced pre‑ and post‑processing methods using emerging technologies such as prompt engineering.
Proficient in processing structured, semi‑structured, and unstructured data from PDFs and scanned documents.

Required Skills:

6–8 years of experience in data science, analytics, or statistical modelling roles.
Strong foundation in data analytics, feature engineering, NLP, predictive modelling, LLMs, and RAG workflows.
Expertise in Python and core ML/DL libraries (TensorFlow, PyTorch, Scikit‑learn), with demonstrated experience in developing and productionizing AI models.
Proven ability to apply strong statistical analysis skills, including probability and applied statistics, to model development and evaluation.
Experience with Git‑based version control and CI/CD pipelines (GitLab/GitHub runners).
Strong understanding of relational databases, large‑scale data processing, and statistical programming.
Familiarity with MLOps principles and experience deploying solutions on cloud platforms (AWS and/or Azure).
Hands‑on experience with commercial or open‑source data management tools.
Excellent communication and presentation skills, capable of simplifying complex technical concepts for both technical and business audiences, with the ability to present to peers, senior management, and cross-functional partners.
Strong influencing and collaboration skills, supporting cross‑team execution and alignment.
Ability to diagnose and resolve complex technical and business problems using deep analytical and industry knowledge
Ability to set and uphold coding standards.
Hands-on experience with leading commercial or open-source data management tools.
Broad business awareness and understanding of relevant internal business relationships.

Preferred

Experience in large financial services or investment banking environments.
Familiarity with Refinitiv or LSEG products and financial data workflows.
Experience working with global or distributed teams.
Comfort interacting with senior stakeholders, including executives and C‑suite partners.

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.

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.

Senior Data Scientist