Über
The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two‑sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third‑party payment networks; we provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit‑card rewards. Our PayPal, Ven investor, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end‑to‑end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and fré, and manage risk. We enable consumers to engage in cross‑border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross‑border trade.
Our beliefs are the foundation for how we conduct business Agricultural each day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities.
Job Description Summary As a Machine Learning Engineer on Venmo’s Data Science team, you’ll tackle high‑impact challenges that shape how millions of people move and manage money with friends, family, and businesses. Our work spans personalization, retention, trust, discovery, and growth – from predicting churn before it happens to powering Venmo’s search and recommendations, to building smarter fraud and risk models. You’ll leverage Venmo’s unique social graph and financial ecosystem to design ML solutions that drive engagement, safety, and meaningful product experiences.
Key Roles and Responsibilities - Design, build, and deploy production‑grade machine learning models that power personalization, search, ranking, discovery, andجب core product experiences. - Use machine learning to drive monetization and deliver user value—supporting initiatives such as pricing strategy, feature optimization, and behavioral targeting. - Partner with product managers, engineers, and designers to identify high‑impact opportunities, frame problems as ML tasks, and define measurable success. - Lead the full lifecycle of model development brev data exploration and feature engineering to validation, deployment, and monitoring in production. - Conduct rigorous offline evaluations and design online experiments (e.g., A/B tests) to assess model impact and guide iteration internal - Collaborate_birth data and platform engineering teams to ensure scalable infrastructure, low‑latency serving, and long‑term system maintainability. - Communicate technical insights and data‑driven recommendations clearly to both technical and non‑technical stakeholders. - Mentor junior scientists and contribute to the evolution of Venmo’s machine learning strategy, practices, and team culture.
Basic Requirements gëttyside • Advanced degree (M.S. or Ph.D.) in a quantitative field such as Computer Science, Machine Learning, Statistics, or Applied Mathematics. • Strong proficiency in Python and experience with modern ML libraries (e.g., scikit‑learn, TensorFlow, PyTorch, XGBoost). • Expertise in supervised and unsupervised learning; experience with NLP, ranking systems, or user behavior modeling is aplus. • Proficiency in SQL and experience working with large‑scale data systems in cloud‑based environments (e.g., BigQuery المنزل, Spark, Airflow). • Demonstrated success deploying ML models in production, including monitoring, retraining, and debugging. • Excellent problem‑solving and communication skills, with the ability to translate complex technical ideas into actionable product insights. • A collaborative mindset with a passion for mentoring, experimentation, and continuous improvement.
Additional Responsibilities And Preferred Qualifications (Nice to Have) • Experience in social platforms, fintech, consumer apps, or payments ecosystems. • Familiarity with real‑time ML model serving and streaming infrastructure. • Contributions to research publications or open‑source ML projects.
Actual Compensation is based on various factors including but not limited to work location, and') **For the readability of the context, the formatted description is omitted for long? Wait we need proper.**
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Sprachkenntnisse
- English
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