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Tier-1 bank, metro location, and mid-level ML role balanced by niche LLM specialization.
Core ML/AI skills transferable, but banking domain and controls knowledge raise industry specificity moderately.
Explicit 5–8 years, mandatory ML/LLM experience, and regulated banking controls increase filter rigidity.
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Design, develop, and implement AI-powered solutions including large language models (LLMs) and machine learning techniques to address business challenges and automate controls.
Collaborate with cross-functional teams to integrate AI and LLMs into products and workflows, ensuring data governance and compliance.
Monitor and analyze AI model performance, provide insights, optimize algorithms, and stay updated with AI/ML advancements to drive innovation.
Bachelor’s degree in Computer Science, Engineering, Mathematics, Machine Learning, Statistics, or related quantitative field.
5-8 years experience in Data Science roles with expertise in AI, LLMs, and prompt engineering.
Proficiency in Python (including libraries such as Numpy, Pandas, Scikit-learn), experience with ML frameworks like TensorFlow, PyTorch, OpenAI, LangChain, big data platforms (Hadoop, Spark), and SQL databases.
Strong verbal and written communication skills; experience collaborating with technical and non-technical stakeholders.
Experienced in applying AI and large language models in financial services or banking domains (Wealth, Cards, Deposit, Loans, Insurance).
Skilled in algorithm development, statistical modeling, machine learning, and data mining to extract actionable business insights.
Capable of managing data governance and compliance alongside technical development, collaborating effectively across interdisciplinary teams.