Sr Data Scientist
@ PayPal

San Jose, CA
$170,000
On Site
Full Time
Posted 4 days ago

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

Sr Data Scientist at PayPal

PayPal has been revolutionizing commerce globally for more than 25 years by creating innovative financial experiences. With a global, two-sided network, we connect hundreds of millions of merchants and consumers to enable seamless payments and commerce.

Job Description Summary

This role will lead advanced data science model development and implementation. You will work with stakeholders to understand requirements, drive best practices in data science, ensure data quality, and mentor junior scientists.

Essential Responsibilities

  • Develop and implement advanced data science models
  • Collaborate with stakeholders to capture requirements
  • Drive best practices and ensure data quality
  • Mentor and guide junior data scientists
  • Stay updated with the latest trends in data science

Expected Qualifications

Minimum of 3+ years of relevant experience and a Bachelor’s degree or equivalent combination of education and experience.

Additional Information

PayPal is committed to fair and equitable compensation practices and provides a balanced hybrid work model including 3 office days and 2 flexible days. We offer competitive benefits and support an inclusive global community.

Key skills/competency

  • Data Science
  • Machine Learning
  • Model Development
  • Data Quality
  • Stakeholder Collaboration
  • Mentorship
  • Hybrid Work
  • Innovation
  • Algorithm Design
  • Statistical Analysis

How to Get Hired at PayPal

🎯 Tips for Getting Hired

  • Research PayPal's culture: Study mission, values, and recent news.
  • Customize your resume: Highlight relevant data science projects.
  • Apply online: Follow instructions and tailor your cover letter.
  • Prepare for interviews: Review technical and behavioral questions.

📝 Interview Preparation Advice

Technical Preparation

Review advanced machine learning algorithms.
Practice Python and SQL coding challenges.
Study statistical analysis techniques.
Update knowledge on data model optimization.

Behavioral Questions

Describe your mentoring approach.
Explain handling complex stakeholder communications.
Share examples of teamwork under pressure.
Discuss decision-making in data projects.

Frequently Asked Questions