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Senior Data Scientist
1 month ago
At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re 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. We're 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.
About the Team and the Role:
Cloud Data Technologies (CDT) team at eBay is responsible for all the data infrastructure, including experimentation platform and management of end-to-end data lifecycle for all eBay data from onsite to analytics use cases.
We are seeking a Senior Data Scientist who is passionate about driving business impact by utilizing advanced data science methodologies to improve the decision making speed & quality, and produce actionable insights from data. Some of the projects that you have a chance to work on include: ML driven bot traffic detection, building customer profile, various A/B testing methodology improvements like Interleaving tests, sequential testing, bayesian methods.
What you will accomplish:
Lead complex data science projects and model development.
Design and implement advanced statistical models and machine learning algorithms.
Conduct advanced SQL for big data query optimization.
Collaborate with cross-functional teams to define and refine data solution requirements.
Stay updated on industry developments and suggest new technologies or methodologies.
What you will bring:
Master’s degree or Ph.D. in Computer Science, or a quantitative field
5+ years of experience in applied ML prediction, classification and regression
Hands-on experience on web data crawling
Experience in building complex models and model performance evaluation
Proficiency in Python or R, and relevant libraries (e.g., scikit-learn, GBM).
Advanced SQL for big data query optimization
Experience with Hadoop, Spark in cloud platforms.
Excellent problem-solving skills and experience in deploying machine learning models in production environments.
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