Sr Data Scientist

PayPal•Chicago, IL

4d•$142,210 - $221,500•Hybrid

About The Position

PayPal, Inc. seeks Sr Data Scientist in Chicago, IL. This role involves applying advanced analytical and technical skills to research multi-dimensional data sets, implement continuous monitoring protocols, and develop complex algorithmic logics that identify and prevent fraudulent activity on Venmo and PayPal's platforms in real-time. The position requires designing, constructing, and validating statistical models to transform raw transactional data into actionable insights for fraud detection. It also involves leveraging advanced data analytics and statistical methodologies to identify emerging fraud patterns and trends across payment ecosystems, and developing, implementing, and maintaining sophisticated real-time risk assessment solutions that balance organizational loss appetite, user experience metrics, and product financial performance KPIs. Rigorous A/B testing will be conducted to evaluate the effectiveness of fraud detection models and risk controls. The role includes creating and maintaining comprehensive data visualization dashboards, performing detailed root cause analysis of fraud cases and security breaches, and partnering cross-functionally with Product Management and Business Unit organizations. Collaboration with risk product engineering teams to translate complex risk requirements into technical specifications is also a key responsibility. The Sr Data Scientist will develop and document risk frameworks and methodologies, and present complex analytical findings to senior leadership and non-technical stakeholders. Maintaining current knowledge of evolving fraud methodologies, financial industry regulations, and technological advancements in the risk management field is essential. Additionally, the role includes mentoring junior analysts in advanced statistical techniques and fraud detection methodologies.

Requirements

Master’s degree, or foreign equivalent, in Data Science, Information Systems, or a closely related field plus two years of experience in the job offered or a related occupation.
OR Bachelor’s degree, or foreign equivalent, in Data Science, Information Systems, or a closely related field plus five years of progressively responsible experience in the job offered or a related occupation.
Data Analytics (2 years)
SQL (2 years)
Big Query (2 years)
Statistical Analysis (2 years)
Python (2 years)
Tableau (2 years)
Data Mining (2 years)
Data Cleaning (2 years)
Experience supporting new product initiatives (2 years)
Financial analysis (2 years)
Hadoop, Hive, and Jupyter Notebooks (2 years)
GitHub (2 years)
Data warehouse and data pipeline (2 years)

Responsibilities

Apply advanced analytical and technical skills to research multi-dimensional data sets, implement continuous monitoring protocols, and develop complex algorithmic logics that identify and prevent fraudulent activity on Venmo and PayPal's platforms in real-time.
Design, construct, and validate statistical models to transform raw transactional data into actionable insights for fraud detection.
Leverage advanced data analytics and statistical methodologies to identify emerging fraud patterns and trends across payment ecosystems.
Develop, implement, and maintain sophisticated real-time risk assessment solutions that carefully balance organizational loss appetite, user experience metrics, and product financial performance KPIs.
Conduct rigorous A/B testing to evaluate the effectiveness of fraud detection models and risk controls, measuring the statistical significance of results and implementing enhancements based on findings.
Create and maintain comprehensive data visualization dashboards that track key risk metrics, providing stakeholders with actionable intelligence on fraud trends and control effectiveness.
Perform detailed root cause analysis of fraud cases and security breaches, identifying systemic vulnerabilities and developing technical solutions to address them.
Partner cross-functionally with Product Management and Business Unit organizations to support new product launches, conducting thorough risk assessments and creating comprehensive risk mitigation requirements.
Work closely with risk product engineering teams to translate complex risk requirements into technical specifications, ensuring accurate implementation and seamless delivery of fraud prevention capabilities.
Develop and document risk frameworks and methodologies that allow for consistent evaluation and mitigation strategies across diverse product offerings.
Present complex analytical findings to senior leadership and non-technical stakeholders, translating technical concepts into business-relevant insights.
Maintain current knowledge of evolving fraud methodologies, financial industry regulations, and technological advancements in the risk management field, applying this knowledge to continuously improve fraud prevention systems.
Mentor junior analysts in advanced statistical techniques and fraud detection methodologies, supporting knowledge transfer across the risk organization.