Meg Fager, Ph.D.

Meg is a highly experienced data and AI practitioner with over 10 years of expertise across data engineering, generative AI, cloud-native architecture, and machine learning. She delivers complex data and AI initiatives end-to-end, turning ambiguous business needs into reliable, production-ready solutions. With a strong consulting background, Meg brings technical leadership, effective cross-functional collaboration, and a talent for shaping challenging project requirements into clear, actionable outcomes. She is committed to mentorship and is known for quickly mastering new technologies and adapting to evolving domains.

Meg has led a wide range of generative AI, machine learning, and data engineering projects – from building fine-tuned LLM solutions and automated ML pipelines to developing large scale data workflows and modernizing enterprise analytics platforms. Her expertise spans cloud architecture, LLMs, ML/LLMOps, statistical modeling, large-scale data engineering, and modern DevOps practices such as CI/CD and infrastructure as code. She is passionate about producing solutions that are technically rigorous, maintainable, and aligned to long-term organizational goals.

Meg holds a Ph.D. in Statistics and Psychometrics from the University of Kansas, grounding her engineering approach in analytical depth and statistical rigor.

Meg lives in Massachusetts where she enjoys summers fishing and boating on Cape Cod and trying new recipes and cuisines.