We're looking for a Staff Data Scientist to partner with revenue, marketing, and product teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. 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.  

• Evaluate and improve our marketing measurement leveraging techniques such as MMM (Marketing Mix Modeling), MTA (Multi-touch Attribution), and incrementality testing
• Develop descriptive and predictive quantitative models to support optimization of our marketing campaigns
• Leverage internal and third-party tools to gain the data needed for marketing insights
• 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
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of marketing-driven acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize our marketing campaigns for revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 10+ years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Past experience working with marketing analytics and utilizing causal inference for marketing measurement
• 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 such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

• Familiarity with Marketing Mix Models and Marketing campaign attribution
• Experience conducting exploratory analyses on large datasets and summarizing complex information in an easy to understand way

Dropbox takes a number of factors into account when determining individual starting pay, including job and level they are hired into, location/metropolitan area, skillset, and peer compensation.  We target most new hire offers between the minimum up to the middle of the range.

Salary/OTE is just one component of Dropbox’s total rewards package. All regular employees are also eligible for the corporate bonus program or a sales incentive (target included in OTE) as well as stock in the form of Restricted Stock Units (RSUs).

Current Salary/OTE Ranges (Subject to change):• US Zone 1: $210,800 - $248,000 - $285,200.• US Zone 2: $189,700 - $223,200 - $256,700.• US Zone 3: $168,600 - $198,400 - $228,200. Dropbox uses the zip code of an employee’s remote work location to determine which metropolitan pay range we use. Current US Zone locations are as follows:• US Zone 1: San Francisco metro, New York City metro, or Seattle metro• US Zone 2: Austin (TX) metro, Chicago metro, California (outside SF metro), Colorado, Connecticut (outside NYC metro), Delaware, Massachusetts, New Hampshire, New York (outside NYC metro), Oregon, Pennsylvania (outside NYC or DC metro), Washington (outside Seattle metro), Washington DC metro and West Virginia (DC metro)• US Zone 3: All other US locations