7+ years of programming experience for working with data, including manipulation and processing (experience with SQL and Python is a big plus).
7+ years of quantitative data analysis, with the ability to evaluate complex issues in detail and uncover actionable insights.
A Bachelor’s degree in Data Science, Statistics, Computer Science, Quantitative Finance—or at least 7 years of hands-on experience in a similar field.
Hands-on experience working with Large Language Models (LLMs) to generate, refine, evaluate, and analyze text data for real-world applications.
Talent for turning unclear or ambiguous business needs into clear, actionable analytics.
Proficient in communicating findings and sharing insights with cross-functional teams across the business.
A creative mindset for designing innovative features and signals, constantly pushing the limits of existing tools and methodologies.
Proficiency in using data visualization tools like Tableau, Power BI, or similar platforms to analyze data, synthesize insights, and design impactful reports.
Ability to break down complex AI concepts into simple, business-friendly terms, craft compelling narratives that highlight key insights, and deliver impactful presentations to key stakeholders.
Familiarity with data engineering tools and practices, including building data pipelines, designing data models, and developing aggregation strategies to power responsive and interactive data products.