Lead Data Scientist

About the position

At PayPal, we continue to push the boundary of what technology can help people around the world accomplish. For that, we are seeking far and wide for that select handful of exceptional world-class problem solvers with a passion for data insights and a relentless execution focus. The Global Analytics and Data Science team is seeking a Lead Data Scientist in Checkout Analytics.

Responsibilities

• Partner closely with Product Managers to understand new product offerings being built and recommend the right metrics to measure the performance of those features
• Identify key metrics, conduct rigorous explorative data analysis, create executive facing dashboards and build business cases that drive decision making and business prioritization
• Analyze identity product performance and health, triage issues, and provide recommendation on the best course solution and optimization
• Synthesize large volumes of data with attention to granular details and present findings and recommendations to senior-level stakeholders
• Guide and mentor group of team members on day-to-day delivery
• Define and cultivate best practices in analytics instrumentation and experimentation
• Support multiple projects at the same time in a fast-paced, results-oriented environment
• Provide strategic and tactical guidance on specific data elements that need to be tracked to enable tracking of metrics and assess user behavior
• Collaborate with data platform teams to build/enhance necessary data platforms to provide metrics & business insights and build alerts to monitor those metrics

Requirements

• 6+ years of experience analyzing large, multi-dimensional data sets and synthesizing insights into actionable solutions
• Data driven mindset with a Bachelor's or Master's and a PhD degree in any quantitative discipline such as Analytics, Engineering, Computer Science, Economics, Statistics or Mathematics
• Fluent in SQL, Excel, and visualization tools such as Tableau or Qlikview; experience with a statistical programming language like R or Python preferred
• Experience analyzing very large, complex, multi-dimensional data set
• Experience with one or multiple of the following will be highly desirable; Jupyter Notebooks, Teradata, Hadoop/Hive, SQL, BigQuery
• Domain expertise in payments or other financial services
• Exceptional communication skills, both written and verbal, to influence cross-functional teams
• Prior work experience in a product analytics space would be highly valued
• A passion for problem-solving and comfort with ambiguity

Benefits

• Flexible work environment
• Employee shares options
• Health and life insurance
• Annual performance bonus
• Equity
• Medical, dental, vision, and other benefits