Responsibilities: Analyze product usage and engagement data (e.g., retention, conversion, feature adoption) to identify trends and actionable insights; Support design and evaluation of A/B tests or feature experiments; compute lift, assess statistical significance, and help interpret outcomes; Conduct exploratory data analysis using SQL and Python to detect patterns, anomalies, or feature-driven behaviors; Create dashboards, visualizations, and summary reports to communicate findings to product, engineering, and design teams; Collaborate cross-functionally with product managers and engineers to implement metrics and iterate on insights; document analysis and methodologies. Minimum Qualifications: Currently pursuing a PhD in Computer Science, Statistics, Econometrics, Mathematics or other quantitative disciplines; Proficient in data analysis tools and languages such as SQL, Python, or R; Practical experience with data querying and scripting languages (e.g.