What You’ll Do:

• Be a strong partner to cross-functional teams in understanding the extent and severity our users’ pain points, especially through quantitative methods & approaches. 
• Provide cross-functional teams visibility into key business KPIs and metrics by developing and presenting reports and dashboards. 
• Independently conduct analyses using rigorous analytic methods and build recommendations that drive decision making and business prioritization 
• Execute upon experimentation roadmaps by implementing experiments and tests, monitoring results and presenting recommendations 
• Generate and share actionable insights with Director+ level leadership via written artifacts such as decks and memos, and verbally in forums such as weekly standup meetings. 

Who You Are:

• BA/BS in a quantitative discipline like Math, Computer Science, Economics or Analytics required. MS in Business Analytics highly preferred. 
• 8+ years of hands-on experience in business and/or product analytics, working with large, multi-dimensional datasets, preferably at fast-growing tech companies. 
• Exceptional communication skills, both verbal and written.  
• Skilled in extracting and transforming data from Snowflake warehouse using SQL  
• Hands-on experience in designing, building, operating, and maintaining Tableau dashboards  
• Knowledge of consumer app businesses and familiarity with concepts such as NPS is preferred.  
• Experience in experimentation (A/B tests, geo tests etc.) and basic statistics (e.g hypothesis testing) required.
• Knowledge of commonly used analytic methods such as regression, decision trees and forecasting is highly preferred.  
• Experience in and ability to play “trusted advisor” to senior and executive leadership and help make change happen. 
• Fast learner.
• Being a fast learner also means the ability to admit defeat, ask for help and iterate quickly so you can learn from your mistakes and move ahead.  
• Respectfully candid with the ability to collaborate with multiple stakeholders as well as peers on the data team   
• Resourceful and scrappy with the ability to deliver insights to the right teams in a timely manner.