PayPal Data Scientist 

India, Karnataka, Bengaluru 

420465853

What you need to know about the roleEach Data Scientist on this team has full ownership of a portfolio of a product and is responsible for end-to-end management of loss and decline rates. Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets.

Job Description:

You will be the Data Scientist in the Fraud Risk teamwhere you will work on leading new projects to build and improve the Risk strategies to prevent fraud using the Risk tooled and custom data & AL/ML models. In this position, you will be partnering with the corresponding Business Units to align with and influence their strategic priorities, educate business partners about Risk management principles, and collaboratively optimize the Risk treatments and experiences for these unique products and partners.

Your day to day

• In this role you will have full ownership of a portfolio of merchants and is responsible for end-to-end management of loss and decline rates.

• Collaborate with different teams to develop strategies for fraud prevention, loss savings, and optimize transaction declines or improve customer friction.

• You will work together with cross-functional teams to deliver solutions and providing Risk analytics on frustration trend/ KPIs monitoring or alerting for fraud events.

• These solutions will adapt PayPal’s advanced proprietary fraud prevention tools enabling business growth.

What do you need to bring

• 3-6 years of relevant experience working with large-scale complex dataset.

• Strong analytical mindset, ability to decompose business requirements into an analytical plan, and execute the plan to answer those business questions

• Excellent communication skills, equally adept at working with engineers as well as business leaders

• Want to build new solutions and invent new approaches to big, ambiguous, critical problems Strong working knowledge of Excel, SQL and Python/R

• Technical Proficiency: Exploratory Data Analysis and expertise in preparing a clean and structured data for model development.

• Experience in applying AI/ML techniques for business decisioning including supervised and unsupervised learning (e.g., regression, classification, clustering, decision trees, anomaly detection, etc.).

• Knowledge of model evaluation techniques such as Precision, Recall, ROC-AUC Curve, etc. along with basic statistical concepts

Our Benefits:

Any general requests for consideration of your skills, please