International Product Growth Scientist

Responsibilities:Identify and measure success of international product growth efforts through goal setting, forecasting, monitoring, and reporting of key product metrics to understand local market trends and insights Apply technical skills with quantitative analysis, experimentation, data mining, and the presentation of data to develop international product growth strategies Work with large and complex data sets to solve a wide array of meaningful problems using different analytical and statistical approaches Partner with International Product Growth Managers, engineers, product managers, designers, data scientists, researchers, and other cross-functional teams to inform, influence, support, and execute international growth strategy and investment decisions across products Skills:Analytics & Data Skills: Strong proficiency in data analysis, including experience with SQL, Python, or R for querying and manipulating large datasets. Ability to design, execute, and interpret analyses to inform product strategy and business decisions. Product & Marketing Acumen: Understanding of product growth strategies, especially in international markets. International Experience: Experience working on products or projects targeting international markets, or personal experience living/studying outside of home country. Awareness of regional trends, cultural nuances, and market-specific challenges Cross-Functional Collaboration: Strong communication skills to translate data insights into actionable recommendations for diverse stakeholders.Education/Experience: - Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. 3+ years of work experience in analytics or 2+ years of experience with a Masters Degree Capacity to work with teams based outside of North America across multiple time zones Experience with data querying languages (e.g. SQL) and A/B testing statistics knowledge Experience performing analyses with minimal direction to answer ambiguous open ended questions