ML Data Scientist, Payments
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Monthly Salary:
Posted on:
4 hours ago
Vacancies:
1 Vacancy
Job Summary
At eBay were more than a global ecommerce leader were changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. Were committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
Our customers are our compass authenticity thrives bold ideas are welcome and everyone can bring their unique selves to work every day. Were in this together sustaining the future of our customers our company and our planet.
Join a team of passionate thinkers innovators and dreamers and help us connect people and build communities to create economic opportunity for all.
At eBay payments are at the heart of every transaction. As an ML Data Scientist on our Payments Engineering team youll help design and build the ML systems that secure and optimize financial transactions for millions of users worldwide. This is a unique opportunity to apply state-of-the-art machine learning from deep learning to generative AI models in a large-scale high-traffic e-commerce environment. Youll work closely with other engineers data scientists and product leaders to create real-time intelligent systems that make buying and selling on eBay safer and more seamless. This role emphasizes designing new algorithms publishing innovative work and pushing the boundaries of AI research while applying these breakthroughs to real-world problems.
What you will accomplish:
Build Train and deploy ML models for intelligent payment routing personalization and intelligent decisioning in payments.
Perform feature engineering data preprocessing and large-scale data analysis.
Research design and implement novel machine learning and AI algorithms across areas such as deep learning generative models reinforcement learning NLP or computer vision.
Design train and optimize machine learning models for a variety of business applications (classification regression recommendation and personalization).
Construct robust ML pipelines for training validation and deployment using modern ML stacks.
Apply prompt engineering techniques with Generative AI models (LLMs diffusion models etc.) to tackle application-driven problems.
Leverage vector databases and build/optimize embeddings for search retrieval and semantic understanding.
Conduct large-scale experiments develop benchmarks and evaluate new approaches against existing solutions.
Stay at the forefront of ML research proactively identifying emerging techniques that can create business and product advantages.
Knowledge Sharing: Contribute to internal technical discussions mentoring and sharing research insights with engineering teams.
Prototype new approaches and publish in leading ML conferences/journals when applicable.
Collaborate with engineers and product teams to build robust ML-powered applications.
What You Will Bring:
4 Years of applied research experience in machine learning or AI
Proficiency in Python and ML libraries/frameworks (e.g. PyTorch TensorFlow JAX).
Strong mathematical and algorithmic background (optimization probability statistics linear algebra).
Solid foundation in statistics predictive modeling and information retrieval.
Experience with large-scale experimentation distributed training and working with big data systems.
Familiarity with real-world applications such as LLM NLP computer vision or recommendation systems.
Knowledge of statistical techniques including regression time series analysis hypothesis testing combining disparate data sources.
Expertise with applying predictive modeling techniques statistics and information retrieval methods to real-world data
Hands on experience with SQL/Hive/Spark data mining and big data query optimization
Extensive experience with large data sets and data manipulation.
Excellent problem-solving skills and experience in deploying predictive models in production environments.
Education: MS or Bachelors in Computer Science Machine Learning Statistics or related field
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Required Experience:
IC
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
About Company
Founded in 1995 in San Jose, Calif., eBay (NASDAQ: EBAY) is where the world goes to shop, sell and give. Whether you’re buying new or used, common or luxurious, trendy or rare – if it exists in the world, it’s probably for sale on eBay. Our great value and unique selection help every ... View more
