Data Scientist, Dropbox

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 5+ years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets
• Deep understanding of statistical analysis, modeling, and common analytical techniques like regression
• Strong analytical thinking, problem-solving skills, and attention to detail
• Excellent communication skills with the ability to articulate complex data concepts clearly to diverse stakeholders
• Proficiency in Python, R, SQL, and familiarity with data visualization tools such as Tableau or Power BI

Desirable

• Dropbox is building a world class Finance organization driven by data and analytics
• The Revenue and Growth Finance team delivers quantitative forecasts and analytic insights that drive the strategy and growth of the entire company
• We're looking for a Data Scientist to partner with finance and product teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives
• An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company
• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Ensure data integrity and compliance with regulatory and internal policies
• Work with cross-functional teams (including Finance, Data Science, Engineering, Product, Engineering, User Research, and senior executives) to rapidly execute and iterate