Data Science

Key Responsibilities:
Team Leadership
• Lead a team of 5–10 data scientists, managing hiring, performance reviews, skill development, and resource planning.

LLM Strategy & Execution
• Define and implement AI strategies using NLP and LLMs to scale automation and intelligence across business units.

Project Ownership
• Drive end-to-end delivery of AI initiatives—from scoping to deployment—in collaboration with product and engineering teams.

Innovation & Partnerships
• Engage with academic and industry partners to pilot emerging technologies (e.g., multimodal LLMs, AI agents) and generate IP (patents, papers).

Technical Expertise:
LLMs & NLP
• 5+ years of NLP experience, including 2+ years leading LLM-focused projects (e.g., chatbots, document understanding).
• Skilled in prompt engineering and fine-tuning techniques (LoRA, P-tuning); hands-on with GPT-4, Claude, LLaMA models.

Engineering & Deployment
• Proficient in LangChain, LlamaIndex, and MLOps tools like MLflow and DVC.
• Experience optimizing LLM APIs for latency and throughput; designing A/B testing frameworks.

Business Alignment
• Ability to translate technical outputs into business impact (e.g., cost savings, process efficiency).
• Strong focus on ROI and prioritization of high-value initiatives.