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Tier-1 brand and visible Senior Data Scientist title, but senior niche GenAI focus reduces applicant density.
Requires specialized ML/GenAI production and evaluation experience, limiting easy cross-industry transferability.
Explicit 10+ years, mandatory ML/LLM hands-on experience, cloud and productionization requirements enforce strict filters.
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Lead end-to-end delivery of data science projects involving problem framing, modeling, evaluation, and iteration specifically for Generative AI and machine learning solutions.
Drive development, optimization, and evaluation of ML and LLM systems including RAG-based and agentic application solutions to ensure production readiness and measurable quality.
Collaborate cross-functionally with AI/ML engineers, data engineers, and platform teams to productionize models, establish best practices for experimentation and governance, and mentor data scientists.
Overall professional experience: 10+ years; with 8+ years of experience and 5+ years hands-on Python for data science/ML.
Bachelor’s or Master’s degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or related field.
Practical experience with LLMs/Generative AI (e.g., GPT, BERT), including model fine-tuning and evaluation methodologies.
Hands-on experience with Azure or AWS cloud ML/AI services and tooling; role requires on-premise work schedule.
Experienced in shaping end-to-end ML/GenAI solutions influencing architecture and production deployment decisions at senior level.
Familiar with evaluation frameworks for LLMs, RAG systems, and agentic applications, with focus on measurable quality and continuous improvement.
Proven ability to lead cross-functional teams including mentoring data scientists, partnering with engineering, and driving experimentation disciplines.