As a Data Scientist, you will spearhead our efforts to measure and enhance authorization rates for PayPals checkout products. This role is central to our mission, offering you the opportunity to work with cutting-edge technology in a fast-paced environment. You will lead the data science projects for the initiatives that optimize transaction success rates, directly impacting PayPals ability to offer seamless payment solutions to millions of users worldwide.
Your day to day:
Data Analysis and Decision Making:
Utilize large, complex datasets to drive improvements in authorization rates.
Employ advanced analytical and statistical techniques to identify trends, issues, and opportunities.
Perform deep-dive analytics including Causal Inference analysis, Pre-Post analysis, Sensitivity analysis, financial projections, and additional ad-hoc exercises to provide holistic recommendations.
Strategic Influence: Develop and present insights and strategic recommendations to Product and Data Science leadership. Influence product direction and strategic decisions through data-driven insights.
Collaboration and Communication: Work closely with cross-functional teams, including product development, engineering, and marketing to implement data-driven improvements. Occasionally collaborate with merchants to optimize their authorization processes. Mentor junior team members .
Innovation and Improvement: Lead initiatives to refine existing analytical processes and develop new approaches to business challenges. Promote a culture of continuous improvement and testing.
What do you need to bring:
5+ years of experience in analyzing multi-dimensional datasets and creating actionable business solutions.
Strong educational background with a Bachelor s/Master s degree in Computer Science, Economics, Statistics, Mathematics, or a related quantitative discipline.
Expertise in SQL, Excel, and visualization tools such as Tableau or Qlikview. Proficiency in a statistical programming language like R or Python is preferred.
Demonstrable experience with big data technologies such as Teradata, Hadoop/Hive, and BigQuery.
Knowledge of Python, Jupyter Notebooks, and SQL.
Exceptional communication skills to effectively articulate insights and influence cross-functional teams.
Prior experience in performing data science to fuel insights to drive Product within a high-tech environment.
Personal Attributes:
A data-driven decision maker, passionate about solving complex problems using analytical solutions.
A self-starter who is motivated to take initiative and thrive in a fast-paced environment.
A fun-loving team player who brings energy and enthusiasm to the workplace.
Comfortable with ambiguity and uncertainty in a dynamic business landscape.
