Data Scientist

About PayPal: PayPal is revolutionizing commerce globally, empowering consumers and businesses in approximately 200 markets to thrive. Its expansive two-sided network connects millions of merchants and consumers, enabling simple, secure, and personalized transactions online and in person. PayPal offers proprietary payment solutions, allowing flexible use of various funding sources and facilitating peer-to-peer transfers through products like PayPal, Venmo, and Xoom. Merchants benefit from end-to-end payment solutions, instant fund access, and tools to manage customer relationships and risk, including simplifying cross-border trade.

Role Summary: This role focuses on developing and implementing data science models and algorithms to address business needs in Bengaluru/Bangalore, India. The Data Scientist will collaborate with stakeholders to define data requirements, ensure data quality, optimize data processes, and deliver effective solutions. Advanced statistical analysis and reporting are key components of this position.

Key Responsibilities:

• Develop and implement advanced data science models and algorithms.
• Analyze and interpret complex datasets to derive actionable insights.
• Ensure the integrity and quality of data used for analysis and model development.
• Collaborate closely with business stakeholders to understand and define data requirements.
• Optimize data processing workflows for enhanced efficiency and performance.
• Conduct advanced statistical analysis and generate comprehensive reports.

Required Qualifications:

• Minimum of 2 years of relevant professional experience and a Bachelor's degree or equivalent practical experience.

Preferred Qualifications & Additional Responsibilities:

• Strong technical and data-mining skills, with experience handling large data volumes using tools like SQL, SAS, Hadoop, Python, or R.
• Proven ability to translate data into business decisions and results.
• Demonstrated business acumen, with creative and strategic thinking capabilities.
• Possess strong analytical, intuitive, and organized thinking skills for detailed data analysis.
• Proactive, self-starter with the ability to drive projects independently and focus on high-impact tasks.
• Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or a related field, with 2-3 years of experience; or a Master's degree with 1-2 years of experience, preferably in risk management, data science, loss forecasting within the payments, banking, or financial services industry.
• Proficiency in SQL for querying relational databases.
• Experience with at least one statistical programming language (SAS, R, Python).
• Familiarity with reporting tools such as Tableau, Power BI, or Qlik is highly desirable.
• Experience with predictive modeling techniques including Regression, Classification, Time Series Forecasting, and NLP.
• Skilled in structuring analyses to solve business problems using data and analytics tools and techniques.