Data Scientist

Role Description

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.

Responsibilities

• 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

Requirements

• 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

Preferred Qualifications

• Advanced degree (Masters or PhD) in a quantitative discipline such as Statistics, Data Science, Economics, or a related field.

Compensation