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Tier-1 brand, popular Data Scientist title, mid-level experience band, and Bangalore location increase applicant competition.
Role requires domain familiarity with financial data and Refinitiv/LSEG products, so industry-specific fit is important.
Explicit 6–8 years plus mandatory ML/LLM, Python, DL frameworks, MLOps, and cloud production experience makes filters strict.
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Own the product vision and execution for a data management framework including data acquisition, cleaning, transformation, and workflows in financial analytics.
Support end-to-end AI/ML lifecycle from problem definition through deployment and continuous improvement of production-grade AI models, optimizing accuracy and scalability.
Collaborate with domain experts, engineering, and project teams to unify tools into integrated workflows, communicate progress with stakeholders, and stay current on financial analytics market and emerging technologies.
6-8 years of experience in data science, analytics, or statistical modelling roles.
Master’s degree in Statistics, Mathematics, Computer Science with Data Science certification, or Engineering degree specializing in Data Science and AI.
Proficiency in Python and ML/DL libraries (TensorFlow, PyTorch, Scikit-learn); experience with cloud platforms (AWS and/or Azure) and MLOps.
Strong foundation in NLP, large language models, RAG workflows, statistical analysis, version control (Git), CI/CD pipelines, and data management tools.
Experienced in financial services or investment banking environments with familiarity of financial data workflows (preferably Refinitiv or LSEG products).
Skilled communicator able to present complex technical concepts to senior stakeholders including executives and cross-functional teams.
Hands-on with both classical and deep learning models, cloud-based AI/ML deployments, and capable of setting coding standards and technical direction in multi-disciplinary teams.