3–5 yrsBengaluruOn-siteDirect career pageEst. 18–28 LPA
Posted 10h ago
Reach people at London Stock Exchange Group (LSEG)
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at London Stock Exchange Group (LSEG) you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Develop and maintain enterprise-grade data management frameworks and advanced analytics workflows for financial data.
- Build, train, validate, and deploy machine learning models including NLP, LLMs, and Retrieval-Augmented Generation, applying MLOps and CI/CD best practices on cloud platforms.
- Collaborate closely with operations, analytics domain experts, and engineering teams to translate business requirements into scalable data and AI solutions and communicate insights to stakeholders.
Minimum Requirements
- 3–5 years of experience in data science, analytics, or statistical modelling roles.
- Master's degree in Statistics, Mathematics, Computer Science, or Engineering with Data Science specialization; Data Science certification required.
- Strong proficiency in Python, data science libraries (Pandas, NumPy, Scikit-learn), and deep learning frameworks (TensorFlow or PyTorch).
- Experience with cloud platforms (AWS/Azure), MLOps, CI/CD pipelines, Git, and working with complex financial or large datasets.
Ideal Candidate Profile
- Experience working with financial services data, preferably with Refinitiv or LSEG datasets and workflows.
- Skilled in translating business needs into technical data solutions within cross-functional and distributed teams.
- Capable of developing and operationalizing advanced NLP and machine learning workflows, balancing technical rigor with business impact.