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.

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.

Stay informed on financial analytics market trends to maintain a forward‑looking, future‑ready strategy.

Continuously learn and adapt to emerging technologies 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.

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.

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.

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.

Ability to set and uphold coding standards.

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

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.

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..

Join us and be part of a team that values innovation, quality, and continuous improvement. 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. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.

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. LSEG offers a range of tailored perks 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 (AI/ML) (Bengaluru)
🏢 LSEG
📍 Bengaluru