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Metro location plus broad ML/GenAI skill requirements create moderate competition.
Highly specialized ML/GenAI and LLM expertise limits cross-industry transferability, increasing background sensitivity.
Explicit 10+ years plus mandatory ML/GenAI, cloud and MLOps tool expertise enforces high strictness.
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Design, develop, and deploy advanced ML models including classical algorithms, deep learning, NLP, and Generative AI to solve complex business problems.
Architect and implement Retrieval-Augmented Generation (RAG) systems and collaborate with data engineers to build scalable data pipelines.
Mentor junior data scientists, present insights to stakeholders, and translate business challenges into impactful data science solutions.
10+ years of experience in data science, machine learning, and AI.
Strong academic background in Computer Science, Statistics, Mathematics, or related field; Master’s or PhD preferred.
Proficiency in Python, SQL, ML libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face), and experience with NLP and GenAI tools (e.g., Azure AI Foundry, GPT, LangChain).
Hands-on experience with Retrieval-Augmented Generation (RAG) systems and familiarity with cloud platforms (Azure preferred) and MLOps tools.
Experienced in leading technical teams and mentoring junior data scientists within a large, global, fast-paced digital technology environment.
Strong expertise in advanced ML techniques including LLM fine-tuning, prompt engineering, and GenAI safety frameworks preferred.
Demonstrated ability to bridge technical and business domains, effectively communicate insights, and innovate within consulting or enterprise SaaS domains.