Sr Data Scientist
@ PayPal

Bangalore, Karnataka, India
On Site
Full Time
Posted 3 days ago

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XXXXXXXXXX XXXXXXXXXXX XXXXXXXXX******* @paypal.com
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Job Details

About PayPal

PayPal has been revolutionizing commerce globally for over 25 years. The company provides innovative payment solutions that enable consumers and businesses to move money, sell, and shop in a secure, personalized, and simple manner across approximately 200 markets.

Job Summary

The Sr Data Scientist will lead the development and implementation of advanced data science models and algorithms. You will work closely with stakeholders to understand requirements and deliver high quality, scalable solutions.

Essential Responsibilities

  • Lead the development and implementation of advanced data science models.
  • Collaborate with stakeholders to understand business and technical requirements.
  • Drive best practices in data science and ensure data quality.
  • Mentor and guide junior data scientists.
  • Stay updated with the latest trends in data science.

Minimum Qualifications

At least 5 years of relevant work experience along with a Bachelor’s degree or equivalent practical experience.

Work Arrangement & Benefits

This role operates under a balanced hybrid work model: 3 days in the office to collaborate in-person, and 2 days remotely, allowing flexibility while ensuring effective teamwork. PayPal offers competitive benefits including flexible work environment, employee share options, and comprehensive health and life insurance.

Key skills/competency

Sr Data Scientist, Data Science, Advanced Modeling, Algorithm, Stakeholder, Data Quality, Mentorship, Hybrid, Innovation, Collaboration

How to Get Hired at PayPal

🎯 Tips for Getting Hired

  • Research PayPal's culture: Review mission, values, and recent projects.
  • Customize your resume: Highlight advanced analytics and leadership experience.
  • Network on LinkedIn: Connect with current PayPal data scientists.
  • Prepare technically: Focus on data models and algorithm case studies.

📝 Interview Preparation Advice

Technical Preparation

Review advanced statistical modeling techniques.
Practice algorithm development and machine learning.
Brush up on data quality and validation methods.
Study real-world case studies in data science.

Behavioral Questions

Describe teamwork in high-pressure projects.
Explain conflict resolution scenarios succinctly.
Discuss leadership experiences with junior colleagues.
Detail collaborative problem-solving with stakeholders.

Frequently Asked Questions