Job Description

Time Type:

Full time

At PayPal (NASDAQ: PYPL), we believe that every person has the right to participate fully in the global economy. Our mission is to democratize financial services to ensure that everyone, regardless of background or economic standing, has access to affordable, convenient, and secure products and services to take control of their financial lives.

Job Description Summary:

What you need to know about the role- You will be a Product Analytics expert ready to take on challenging problems, conducting rigorous data, user behavior analysis to help root cause, understand key metrics and improve customer experiences in a critical PayPal Product area that touches all PayPal users. Meet our team You will be part of the Product Analytics team for Strategic and Shared Services Team focused on Global Identity, Resolutions and Trust to accelerate the positive impact on PayPal customers’ experiences and delivering against enterprise priorities. You will work alongside the brightest Product Management, Engineering Data Science and Engineering talent, tackling interesting analytics problems in the space of Risk

Job Description:

Your way to impact  

Who are we looking for? 

• You are curious, inquisitive and excited about digging into data to uncover insights and answer business questions 

• You are hyper-analytical and intellectually honest truly believing in data-driven decisions and communicating your ideas through storytelling  

• You are a highly motivated, result-oriented self-starter, enjoy working in a fast-pace environment, and can deliver successful results with minimal guidance 

• You are a energized, fun-loving, adventurous team player 

Your day to day  

In your day to day role, you will 

• Become a domain expert in your Product area that touches all Paypal users and conduct rigorous data analysis in the area to help root cause, understand key metrics and improve customer experiences 

• Cross functional Collaboration - Partner with Product Management, Engineering, Data stakeholders in the areas of Risk/Compliance Back office, Disputes and Resolution to effectively build structured, analytics solutions enabling understanding of Customer behaviour and driving data informed decisions on Product/feature optimization 

• Translate business questions to analyses, conduct exploratory/investigative data analyses, identify key metrics, establish cause & effect, demonstrate great attention to detail, provide coherent and holistic recommendations based on data or experiment results 

• Roll up your sleeves and work with large quantities of data using SQL and Excel, statistical programming languages like R or Python, and visualizing content through reporting tools such as Tableau, Qlikview etc., 

• Build exec-facing insights, reports, and dashboards to track the key performance indicators of individual products/initiatives as well as overall business 

• Present findings and recommendations to Senior-level, Technical and Non-Technical stakeholders 

• Demonstrate exceptional communication skills, both written and verbal 

• Be comfortable with frequent context-switching in a fast-paced, results oriented environment 

What do you need to bring-  

• Data driven mindset with a degree in any quantitative discipline such as Engineering, Computer Science, Economics, Statistics or Mathematics 

• 3-5 years of experience analysing large, multi-dimensional data sets and synthesizing insights into actionable recommendations  

• Exceptional communication skills, both written and verbal, to influence cross-functional teams. 

• Fluent in SQL, Excel, and visualization tools such as Tableau or Qlikview; experience with a statistical programming language like R or Python preferred 

• Domain expertise in the area of Payments or other consumer financial products, Product Analytics, Experimentation (A/B testing) 

• Prior work experience in Product/Business/Risk analytics space would be highly valued 

Prior Experience/Knowledge in Case Management tools, Resolutions and Protections domain is a plus 

• Experience/Knowledge of statistical data mining would be a plus 

• Experience/Knowledge of statistical data mining would be a plus