Dropbox is a leading global collaboration platform that's transforming the way people work together, from the smallest business to the largest enterprise. With more than 500 million registered users across more than 180 countries, our mission is to design a more enlightened way of working. From our headquarters in San Francisco to eight dedicated Studios and a worldwide team of employees who choose where they work best, our Virtual First approach is leading the way into the future of work.
Our Sales and Channel teams share Dropbox Business with companies around the world, helping them understand the power Dropbox has to offer teams at scale. The Sales Strategy team develops insights to assess business performance, and leads initiatives to identify new sources of growth. We work closely with senior sales leaders to develop shared goals, and do the planning and execution necessary to make those goals a reality.
As a GTM Intelligence Analyst, you will play a crucial role in areas such as analytical hypothesis validation, business case building, and creating data-driven targeting solutions to help our sales teams find the best opportunities to land, expand, and retain our customers. You will liaise with senior revenue leaders to define priorities, and work with a number of teams across the business to learn more about our customers, and deliver thoughtful analytical solutions.
The ideal candidate is a self-starter, independent thinker, deeply analytical, and not afraid of carving a path forward in ambiguous situations. You will relish the chance to roll up your sleeves, get to grips with vast datasets, deeply understand our go-to-market strategy, and propose bold, innovative solutions to a wide variety of problems.
- Running strategic analyses to validate hypotheses for our revenue leadership team
- Building business cases based on historical usage and purchase trends, to advocate for new ways to go to market
- Developing scoring systems to help our sales teams prioritize which customers to talk to, and which products to recommend
- Working with our machine learning team to develop propensity models to understand holistic account health, and identify potential deployment and churn risks
- Experience in analysis or data science for a technology company
- Strong analytical skills: fluency with Excel/Tableau, and experience working in SQL (Hive/Snowflake)
- [Nice to have] Deeper technical skills: background in statistical modelling/programming (Python/R), data science, experimentation, or software engineering (with a focus on workflow automation); understanding of basic machine learning techniques (regressions, tree-based models, clustering, SVMs)
- [Nice to have] Experience supporting the sales process for a SaaS company (e.g. as a sales engineer/solutions architect)
- Strong communication skills: ability to craft a data-driven narrative for audiences for a variety of technical skills; the ability to influence without authority and act as an evangelist for our team as you build relationships with teams across the company
- Creativity and user-centricity: a willingness to learn from our stakeholders, think outside the box, and take bold bets to improve the way we go to market