Business Intelligence Analyst

Responsibilities: - Partner with cross-functional stakeholders (product, marketing, content, revenue) to translate business questions into analytical frameworks and deliverables - - Build and maintain dashboards, reports, and self-serve analytics tools that support day-to-day decisions - - Conduct deep-dive analyses to surface trends, opportunities, and risks across engagement, monetization, audience growth, and content performance - - Design and analyze experiments (A/B tests, feature rollouts) to validate hypotheses and quantify business impact - - Develop forecasting and quantitative models to support both short-term planning and long-term strategy - - Define and standardize key metrics across teams, ensuring consistency in how the business measures success - - Collaborate with Data Engineering on data quality, modeling, and pipeline improvements - - Mentor junior analysts and champion data literacy and a data-driven culture across the organization - Qualifications: - 3+ years of experience in business analytics, BI, or data analytics roles (media, digital, or consumer tech industries strongly preferred) - - Strong proficiency in SQL — comfortable writing complex queries, optimizing performance, and working with large datasets in cloud data warehouses (BigQuery, Snowflake, Redshift, or similar) - - Hands-on experience with modern BI/visualization tools (Looker, Tableau, Power BI, Metabase, or similar) - - Working knowledge of Python (or R) for analysis, automation, and statistical modeling - - Solid grasp of statistics, experimentation methodology, and forecasting techniques - - Strong business acumen with deep understanding of media industry metrics (DAU/MAU, retention, ARPU, CTR, watch time, ad revenue metrics, etc.) - - Excellent communication skills — able to translate complex analyses into clear narratives for both technical and non-technical audiences - - Self-driven, comfortable with ambiguity, and able to manage multiple priorities under tight deadlines - Nice to Have: - Familiarity with data modeling concepts and tools like dbt - - Experience with version control (Git) and code-based analytics workflows - - Exposure to machine learning or predictive modeling - - Prior experience mentoring analysts or leading analytics projects end-to-end -