Job Summary:

Job Description:

PayPal, Inc. seeks Senior Data Scientist in Chicago, IL

Job Duties: Lead the development and implementation of advanced data science models. Design and implement core decision models for identity, onboarding, authentication, abuse, scam, product-specific models by leveraging Python, SQL languages, and BigQuery tool to design and implement risk decision. Collaborate with stakeholders to understand requirements. Work closely with cross-functional teams, including engineers, operations, and product teams, to integrate fraud prediction models and strategies into various systems and processes. Drive best practices in data science. Drive success through data-driven approach by applying statistics, machine learning and AI into fraud detection space. Maintain loss within targets while still delivering best-in-class risk experience by optimizing risk frictions and ensuring PayPal customers are kept safe and ensure through machine learning and AI applications. Ensure data quality and integrity in all processes. Ensure data integrity and consistency by working closely with business stakeholders and engineers to address critical data challenges. Validate the underlying data and map out the discrepancies in our system to help improve data quality and integrity by working with data engineering team. Mentor and guide junior data scientists. Provide support to guide junior data scientists in the same team to help them deliver the projects and bridge the knowledge gap. Stay updated with the latest trends in data science. Explore most advanced technologies (AI, ML, LLM) to evolve risk strategies and risk modelling to better combat fraud. Partial telecommuting permitted from within a commutable distance.

Minimum Requirements: Master's degree, or foreign equivalent, in Computer Science, Engineering, Natural and Applied Science or a closely related field plus two years of experience in the job offered or a related occupation Employer will accept a Bachelor's degree, or foreign equivalent, in Computer Science, Engineering, Natural and Applied Science or a closely related field plus five years of experience in the job offered or a related occupation.

Special Skill Requirements:

1. Applying machine learning algorithms on financial data for fraud detection, abuse detection, identity risk or risk assessment, using supervised learning and unsupervised learning (logistic regression, gradient boosting, random forest, clustering) (2 years)

2. Developing, training, calibrating and validating regression-based default models for fraud or risk prediction (2 years)

3. Conducting analysis using SQL/SAS/Python in database/server for large-scale data analysis (2 years)

4. Performing data manipulation and processing using distributed computing frameworks such as PySpark/Spark for feature engineering, model training, or analytics (2 years)

5. Building scalable data pipelines for analytics or model training using Python, SQL, or cloud-based tools (2 years)

6. Developing, testing, and operating model training or scoring pipelines in Python on cloud environments using distributed computing clusters (2 years)

7. Building and deploying automated dashboards and benchmarks for fraud or risk related metrics monitoring using Python, Tableau, and Snowflake (2 years)

8. Deploying analytical or machine learning models into production and maintain key documentation in production environment on cloud (2 years)

9. Analyzing transactional or behavior data to identify anomalies, patterns or potential fraud indicators using statistical or machine learning methods (2 years)

10. Working with cross-functional teams including risk, engineering, and product partner, to translate fraud business requirements into analytical or model solutions (2 years)

11. Communicating analytical findings, model insights, or fraud trends to different stakeholders (2 years)

Additional Responsibilities & Preferred Qualifications:

The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is:

Primary Location | Pay Range:

Chicago, IL | $153,317.00-221,500.00 per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m.

Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.

Must be legally authorized to work in the U.S. without sponsorship.

Subsidiary:
PayPal

Travel Percent:
0

PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing-physical, emotional, and financial-delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.