Details:

Our global sales transformation is in full swing. We embarked on a path of transforming and building a world class sales organization earlier this year. Our team helps to power PayPal’s high growth Sales organization by delivering actionable insights and business intelligence at scale to all levels of the business - our customers, our front-line Sales teams and our executive leadership team. In this role, you will lead a team to develop solutions for complex, ambiguous and high-visibility business challenges. You will set and execute on a vision for your team that reflects your deep analytical expertise. You will be a thought partner to sales leadership teams. You will partner with these teams to understand the insights they require to manage and grow their business and leverage cross-functional teams to develop and land solutions that meet their needs at scale. You are deeply curious and persistent in gaining knowledge about our products and go-to-market strategy. You will have exposure and visibility to PayPal sales executives, as you work with them to understand their needs and promote solutions that your team develops.

We are a team of entrepreneurial, enthusiastic and client-focused members. If you are a fast learner, are willing to learn and grow, have a can-do attitude and wants to solve problems in the most pragmatic way, we would like to talk with you

Min. Qualification:

10+ years of experience in analytics, engineering or management consulting or equivalent analytical and project management experience

Skills Required:

SQL, Python, R, Tableau, Excel

Roles:

• Accomplished team leader, with experience managing high-performing Data Scientists and Quantitative Analysts
• Experience working within and driving strategy for large, global, complex organizations across multiple stakeholders and teams
• Exceptional problem-solving skills, with strong ability to drive towards action and impact
• Experience in managing analytics projects from inception to delivery, including developing structured solutions. 
• Experience with visualizations, dashboards, and reports
• Experience with data modeling, machine learning algorithms, and data science techniques
• Experience explaining technical concepts and analysis implications to varied audiences and translating business objectives into analyses