Data Scientist

Role Overview

Partner with product, engineering, and design teams to answer key business questions about revenue growth, product optimization, business scaling, monetization, and high-impact initiatives. This role solves challenging problems and drives business growth through deep understanding of user behaviors and applied analytics.

Key Responsibilities

• Develop deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify hypotheses, and design & execute experiments
• Perform exploratory analysis to understand user engagement behavior and derive insights that inform experimentation design and roadmaps
• Create personalized segmentation strategies leveraging propensity models for targeted offers and experiences
• Identify key trends and build automated reporting and executive-facing dashboards to track acquisition, monetization, and engagement metrics
• Extract actionable insights from large, complex, multi-dimensional customer behavior datasets
• Monitor and analyze high-volume experiments designed to optimize product experience and revenue
• Promote best practices for multivariate experiments
• Translate complex concepts into business implications through excellent communication (verbal and written)
• Prioritize ruthlessly and work with cross-functional teams (Data Science, Marketing, Product, Engineering, Design, User Research, executives) to rapidly execute and iterate

Requirements

• Education: Bachelor's degree or above in quantitative discipline (Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field)
• Experience: 3-5 years using analytics to drive key business decisions (business/product/marketing analytics, business intelligence, strategy consulting)
• Proven track record of working independently and proactively engaging with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets (Hadoop)
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques (regression, decision trees)
• Strong background running multivariate experiments to optimize product or revenue flow
• Strong verbal and written communication skills
• Plus: Proficiency in programming/scripting and knowledge of statistical packages (R or Python)

Preferred Qualifications

• Product analytics experience in a SaaS company
• Master's degree or above in quantitative discipline