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Tier-1 brand and metro Bangalore location increase applicant density, but niche ML specialization reduces it.
Role requires ML expertise but prefers financial domain and governance experience, moderately limiting cross-industry fit.
Explicit 8–12 years, senior ML leadership, mandatory ML/NLP/LLM and MLOps skills increase filter strictness.
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Lead and mentor a senior data science team to deliver end-to-end AI/ML solutions including design, development, deployment, and optimization.
Own and evolve a data management and analytics framework integrating diverse data sources and AI technologies focused on financial analytics.
Partner with business and technical stakeholders to translate needs into scalable, production-grade AI solutions leveraging NLP, deep learning, and cloud deployment.
8–12 years of experience in data science or related analytics and statistical modelling roles.
Master’s degree in Statistics, Mathematics, Computer Science with Data Science certification, or Engineering degree specializing in Data Science and AI.
Strong expertise in Python, ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn), large-scale data processing, and cloud platforms (AWS, Azure).
Work Experience Required: 8–12 years specified in the JD.
Experienced in leading multi-disciplinary data science teams delivering AI/ML initiatives in financial or similarly complex regulated environments.
Strong strategic focus on enterprise AI governance, responsible AI compliance, and deployment of production-grade scalable solutions.
Expertise in advanced AI techniques including NLP, LLMs, Generative AI, and Retrieval-Augmented Generation with emphasis on business impact and stakeholder engagement.