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Tier-1 brand and metro location increase competition but niche LLM/agent specialization reduces generalist applicant density.
Specialized ML/LLM, agentic systems and supply-chain impact create strong domain bias and limited portability.
Explicit 7-10 years requirement plus mandatory advanced LLM, statistical, and MLOps skills make screening strict.
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Lead architectural design and development of AI/ML solutions impacting supply chain operations and New Product Introduction (NPI).
Translate business objectives into scalable data science projects and advanced AI models including LLM-powered applications and autonomous workflows.
Drive technical leadership including experimental design, cross-functional collaboration, innovation pilots, and ensure adherence to ethical and reproducibility standards.
Bachelor’s degree in Statistics, Mathematics, Computer Science, Data Science, or related quantitative field.
7-10 years of professional experience in data science, analytics, or related disciplines with expertise in statistical analysis and correlation techniques.
Proficient in generative AI and LLM deployment, including Agentic AI systems, RAG pipelines, prompt engineering, vector databases, and semantic retrieval.
Expert programming skills in Python (Pandas, Scikit-learn, PyTorch/TensorFlow), SQL, and familiarity with data engineering tools (Spark, Snowflake).
Experienced senior data scientist with strong expertise in advanced AI/ML, especially generative AI, agent architectures, and LLM systems applied in operational or supply chain contexts.
Strategic thinker capable of translating business goals into scalable, production-ready AI solutions with an emphasis on system design and governance.
Strong leadership mindset demonstrated by mentoring capabilities, technical rigor, and ability to communicate complex analytics to non-technical stakeholders effectively.