The role involves driving end-to-end data science execution, including data curation, analytics, and modeling to generate actionable insights. The individual will lead a new workstream focused on monitoring AI-relevant trends and advance existing local economic intelligence initiatives. Responsibilities include designing and building data pipelines, integrating complex datasets, and implementing statistical and machine learning solutions. The position requires collaborating with economists and cross-functional stakeholders to identify emerging trends and economic relationships. Additionally, the role entails communicating findings through reports and presentations to senior executive audiences.

Candidates must possess a Master's degree in a quantitative discipline and at least five years of relevant professional experience. Required technical proficiencies include programming in Python, SQL, Spark, or R, alongside deep knowledge of statistics and data mining. Applicants must demonstrate expertise in the GenAI and LLM ecosystem, including familiarity with agentic AI. Furthermore, the role requires the ability to build automated data pipelines and communicate complex quantitative findings to executive audiences.