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Role Description
We're looking for a Staff Data Scientist to partner with engineering 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.
Responsibilities- 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
- Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes
- Identify key trends and build automated reporting & executive-facing dashboards to track the progress of 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 the product for user experience and 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 Data Science, 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
- 8-10+ years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
- 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
Preferred Qualifications
- Master's or Ph.D. Degree in a quantitative field
- Experience with predictive modeling, machine learning, and experimentation/causal inference methods.
US Zone 1
This role is not available in Zone 1
US Zone 2
$197,400—$267,000 USD
US Zone 3
$175,400—$237,400 USD
Dropbox Seattle, Washington, USA Office
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Though remote is our primary way of working, meaningful in-person connection and collaboration is a critical part of Virtual First. Our Seattle Studio is a place for teams to come together to host meetings, off-sites, and build community.
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
