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
3-5 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 is a plus

Data Scientist

Key skills