Sr Data Scientist at PayPal
San Jose, California, United States -
Full Time


Start Date

Immediate

Expiry Date

18 Feb, 26

Salary

0.0

Posted On

20 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Science, SQL, Python, A/B Testing, Machine Learning, Data Analytics, Data Quality, Data Storytelling, Mentoring, Collaboration, Problem Solving, Product Strategy, BigQuery, Hadoop, Teradata, Jupyter Notebooks

Industry

Software Development

Description
Lead the development and implementation of advanced data science models. Collaborate with stakeholders to understand requirements. Drive best practices in data science. Ensure data quality and integrity in all processes. Mentor and guide junior data scientists. Stay updated with the latest trends in data science. 3+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. -Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience. -Strong analytical and problem-solving mindset, with a degree in a quantitative field such as Data Science, Computer Science, Engineering, Statistics, Mathematics, Economics, or a related discipline -4+ years of experience in Product Data Science, including A/B testing and experimentation, advanced analytics, and applied machine learning -Proven track record of partnering with Product teams in domains such as Payments, eCommerce, or SaaS to shape product strategy, inform roadmaps, and deliver impactful data-driven insights -Advanced proficiency in SQL and Python, with expertise in working with large-scale, complex datasets to derive actionable insights -Deep experience analyzing high-volume, high-dimensional real-world data, with a focus on scalability and business impact -Hands-on experience with modern data tools and platforms such as Jupyter Notebooks, BigQuery, Teradata, Hadoop, or Hive is highly desirable -Exceptional communication and data storytelling skills, with the ability to distill complex findings for both technical and non-technical audiences and influence cross-functional decision-making -Highly motivated and self-directed, with a strong passion for experimentation, product thinking, and navigating ambiguity in a fast-paced environment -Prior work experience in Product/Business/Risk analytics space would be highly valued Subsidiary:
Responsibilities
Lead the development and implementation of advanced data science models while collaborating with stakeholders to understand requirements. Drive best practices in data science and ensure data quality and integrity in all processes.
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