Dropbox is the home for your most important stuff—now we’re bringing it to life with a growing family of products. As we scale our global brand, there’s plenty of space for you to grow alongside us and simplify life for millions of people around the world.
Dropbox is looking to become the industry leader in Data Science-driven sales. The Revenue Data Science team will deliver analytics and tools to drive revenue by combining the rich internal data across 500M+ Dropbox users and external data on buying patterns of prospects and customers.
Roles and Responsibilities
- Work on high priority initiatives including (but not limited to) account prioritization, account prospecting, and opportunity scoring.
- Instrumentation of propensity modeling: query and process big data: integrate volumes of data from multiple internal and external sources and into Dropbox’s systems of record
- Partner closely with data scientists to develop internal and external data sources to be used in propensity modeling and predictive analytics.
- Implement propensity models into Dropbox’s revenue systems of record, track their effectiveness, analyze & report on findings.
- Establish scaleable revenue prospecting initiatives using Dropbox internal data
- Conceptualize, design and build data-fueled insights to help Dropbox improve analytics for prospects and customers. Examples include:
- Benchmarking: Develop comparative indexes that measure how companies compare to industry peers in key performance and usage metrics.
- Recommendation engine: Use real-time analytics to recommend ways in which customers can maximize adoption and usage of Dropbox.
- Work closely with other team members and the business to further develop metrics, KPIs, and insight that provides performance improvement.
- Master’s Degree in computer science, applied statistics, economics, data mining, machine learning, or a related quantitative discipline
- 5 - 8 years experience as strategic project/program lead in management consulting, B2B software (ideally SaaS) or a high-growth technology firm
- Experience working with very large semi-structured data sets and integrating them into systems of record
- Good SFDC skills and ability to develop analysis based on CRM data in a scalable manner
- Ability to solve complex analytical problems using quantitative approaches with a unique blend of analytical, mathematical and technical skills
- Highly detailed-oriented and exceptional organizational and follow-through skills a must
- Strong data-oriented scripting (e.g. SQL) and statistical programming (e.g., R or python)
- Excellent judgment and creative problem solving skills
- Excellent at planning and project management – ability to look ahead to meet regular deadlines and prevent last minute fire drills
- Strong desire to take initiative; thrive on change and comfortable with ambiguity
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