PayPal | Data Scientist

Job Description

What you need to know about the role

Seeking a Data Scientist for Pricing & FX Optimization Analytics team who is enthusiastic about problem-solving, adept at generating valuable insights from data through deep dive analysis, experienced at evaluating performance of pricing strategies and initiatives by establishing test and control plans and ensuring constant monitoring is in place.

Meet our team

The Merchant Pricing-FX Analytics & ML team at PayPal plays a critical role in driving acceleration for PayPal’s top and bottom line by using the scientific method to advocate for decisions founded in data-driven insights. This team sits at the intersection of Strategy, Product, and Sales, and has a front-row seat to Senior Leadership discussions on PayPal’s monetization strategy.

Job Description:

Your way to impact  

• This role directly impacts PayPal top and bottom line by contributing to key Pricing Strategy decisions through rigorous analysis and experimentation. 
• Collaborate with cross-functional teams including Sales, Marketing, Pricing Strategy, Operations, Product, and Engineering teams to drive new Pricing and FX ideas through each stage of the idea-lifecyle – from genesis to strategy to execution. 
• You will synthesizing large volumes of data with attention to granular details and present findings and recommendations to senior-level stakeholders  
• You will collaborate with engineering and data engineering to enable feature tracking, resolve complex data and tracking issues, and build necessary data pipelines  

Your day to day  

In your day to day role you will XXX 

• Become a domain expert in Pricing & FX and conduct rigorous data analysis to drive meaningful financial benefit for PayPal without jeopardizing customer experience 
• Perform deep-dive analytics including Causal Inference analysis, Pre-Post analysis, Sensitivity analysis, financial projections, and additional ad-hoc exercises to provide holistic recommendations for segment level Pricing optimizations 
• Challenge the status quo, and drive data backed decision making  
• Partner closely with product leaders 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-friendly info-insight packets and build business cases that drive decision making and prioritization  
• Analyze business performance and health, triage issues, and provide recommendation on the best course solution and optimization  
• Synthesizing large volumes of data with attention to granular details and present findings and recommendations to senior-level stakeholders  
• Collaborate with engineering and data engineering to enable feature tracking, resolve complex data and tracking issues, and build necessary data pipelines  
• Define and cultivate best practices in analytics instrumentation and experimentation  
• Support multiple projects at the same time in a fast-paced, results-oriented environment  
• Mentor junior analysts on complex analyses  

What do you need to bring

• At least 5 years of experience analyzing large, multi-dimensional data sets and synthesizing insights into actionable solutions  
• B.S. in a quantitative field, advanced degrees preferred  
• Fluent in SQL and scripting languages such as Python or R, comfortable working with large, complex, and potentially messy datasets  
• Understanding of statistics (e.g. hypothesis testing, statistical inference, regression) and experience designing and evaluating complex experiments   
• Exceptional communication skills, both written and verbal, to influence cross-functional teams  
• Strong interpersonal skills and experience leading cross-functional teams   
• Prior work experience in a product analytics space would be highly valued  
• A passion for problem-solving and comfort with ambiguity