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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.
Compensation
Canada Pay Range
$181,900—$246,100 CAD
Dropbox Singapore Office
What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
