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Tier-1 brand plus metro location and popular data scientist title increase competition.
Role demands deep ML/GenAI, LLM production, and finance compliance knowledge, limiting cross-industry transfer.
Explicit 12+ years, 8+ years Python, and GenAI productionization requirements create strict filters.
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Lead end-to-end data science delivery for GenAI and ML initiatives including problem framing, modeling, evaluation, and productionization.
Develop and optimize ML and Generative AI solutions, defining evaluation frameworks and ensuring model quality and performance.
Collaborate cross-functionally with engineering, data teams, and stakeholders to transition models into production and mentor data scientists.
12+ years professional experience with 8+ years hands-on Python for applied data science and machine learning.
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field.
Practical experience with LLMs/Generative AI models and strong understanding of evaluation methodologies.
Hands-on experience with cloud ML/AI services, preferably Azure or AWS.
Experienced in managing the full ML model lifecycle from problem framing to production and monitoring in large-scale environments.
Proficient in driving model evaluation, experimentation frameworks, and implementation of RAG-based and agentic AI applications.
Skilled at cross-functional collaboration with engineering and platform teams to ensure scalable, production-grade AI deployments.