Sr Data Scientist

PayPal, Inc.; City of London; On-site; GBP 80,000 - 100,000; Full time

Job summary

A leading fintech company in London is seeking a Senior Data Scientist to design and develop advanced AI models leveraging extensive transaction data. The role involves leading model development, collaborating with stakeholders, and mentoring junior data scientists. Candidates should have over 3 years of experience, strong Python skills, and familiarity with various data science frameworks. The company offers a competitive compensation package and a flexible hybrid work model.

Benefits

Flexible hybrid work model

Competitive compensation

Equity

Health and life insurance

Qualifications

• 3+ years of relevant experience in data science or machine learning.
• Proven ability to build and optimize models at scale.

Responsibilities

• Lead the development and implementation of advanced data science models.
• Collaborate with stakeholders to understand requirements.
• Drive best practices in data science.
• Mentor and guide junior data scientists.
• Stay updated with the latest trends in data science.
• Build scalable machine learning pipelines.
• Contribute to customer segmentation and predictive model optimization.

Skills

Data science experience

Python programming

TensorFlow

Keras

PyTorch

Graph neural networks

Transformer models

Problem-solving skills

Mentoring

Education

BS/BS-MS degree in Computer Science, Statistics, Mathematics, Engineering, or equivalent

Job description

Join PayPal to apply for the Senior Data Scientist role.

PayPal has been revolutionizing commerce globally for over 25 years, enabling consumers and businesses to move money, make purchases, and complete payments securely worldwide.

Job Summary

The Ads Tech team is building PayPal’s next‑generation advertising platform. The Senior Data Scientist will design and develop advanced AI and data science models that leverage the firm’s merchant and transaction data to drive product innovation.

Responsibilities

• Lead the development and implementation of advanced data science models.
• Collaborate with stakeholders to understand requirements and translate them into data‑driven solutions.
• Drive best practices in data science and ensure data quality and integrity across all processes.
• Mentor and guide junior data scientists and foster a collaborative, egoless programming culture.
• Stay updated with the latest trends in data science, including graph neural networks, recommendation systems, and transformer models.
• Build scalable machine learning pipelines using Python, TensorFlow, Keras, PyTorch, and Graph Neural Network frameworks.
• Contribute to customer segmentation, recommendation systems, and predictive model optimization.

Qualifications

• 3+ years of relevant experience in data science or machine learning.
• Strong programming skills in Python.
• Experience with TensorFlow, Keras, PyTorch, graph neural networks, and transformer models.
• Proven ability to build and optimize models at scale and to mentor junior team members.
• Excellent problem‑solving skills and a collaborative attitude.
• BS/BS‑MS degree in Computer Science, Statistics, Mathematics, Engineering, or equivalent experience.

Benefits

PayPal offers a flexible hybrid work model, competitive compensation, equity, health and life insurance, and other employee benefits to support work‑life balance and career growth.

EEO Statement

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at [e-mail].