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.
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Use machine learning to research, design, implement, and validate leading-edge propensity models to analyze large scale network collaboration (e.g., 500M+ users, 35B+ office documents) and micro-segment prospects and customers alike. Examples include:
Account prioritization: segmenting and scoring account lists using propensity-to-buy models that combine Dropbox and external data sources
Account prospecting: generating scaleable analytics & models that link Dropbox data with company characteristics to create sales pipeline
Opportunity scoring: using Bayesian modeling to generate regularly-updating sales opportunity scores
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
Predictive modeling: Build lead scoring algorithms to prioritize and time when account team should engage with which customers
Recommendation engine: Use real-time analytics to recommend ways in which customers can maximize adoption and usage of Dropbox
Work closely with sales and marketing teams to help articulate the value and impact of Dropbox
Requirements:
PhD or Master’s Degree in computer science, applied statistics, data mining, machine learning, operations research, or a related quantitative discipline
8+ years of experience delivering world-class data science outcomes
Experience working with Sales and translating insights for sales is a big plus
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)
Experience with social media analytics is a plus
Excellent judgment and creative problem solving skills
Entrepreneurial team player who can multitask
Exceptional written, oral, interpersonal, and presentation skills and the ability to effectively interface with senior management and staff
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