How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Staff Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.
Joining on the ground floor of this startup team, you’ll partner directly with the Head of Data Science and Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!
Responsibilities- Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
- Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
- Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
- Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
- Identify what matters most and prioritize ruthlessly for the area you will own
- Contribute to a culture of strong technical ownership, coach junior Data scientists in the team, and partner with Head of Data Science to keep evolving DS working model and elevate DS impact
- Work with cross-functional teams (including 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
- 9+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
- Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction
- Proficiency in SQL, Python or other programming/scripting languages
- Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
- Ability to provide data insights and recommendations for 0→1 product even when sample size is small
- Strong verbal and written communication skills
- Experience in startups or building 0→1 products
- Expertise in using data to inform AI/ML product development
- Background in SaaS product and growth analytics
US Zone 1
This role is not available in Zone 1
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What the Team is Saying
What We Do
We're a global community of bold visionaries and resourceful doers who are shaping the future of Dropbox—and with it the future of work. Our Virtual First model combines the flexibility of a distributed workplace with the power of human connection, making space for both meaningful work and meaningful relationships. With our start-up mindset and enterprise-level opportunities, you can be who you are and grow into who you’re meant to be. Here, you can own your impact to make work more intuitive, joyful, and human—for you as a Dropboxer and for hundreds of millions of people worldwide. If you're ready to push boundaries—and yourself—Dropbox is ready for you.
Why Work With Us
We believe people do their best work when empowered with autonomy and harmony, and we understand there’s no substitute for human connection. Our Virtual First model combines the flexibility of remote work with the power of in-person collaboration to create the best of both worlds: a distributed workplace, anchored in community.
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Employees work remotely.
While remote work is the primary experience for our employees, we also prioritize opportunities for quarterly in-person collaboration knowing that connection is vital to a thriving workforce. We focus on how we work, not where we work.
