Data Scientist

3 weeks ago

Dublin, Dublin City, Ireland 0307 eBay Europe Services Ltd Full time

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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 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.

Conduct advanced SQL for big data query optimization.

Design and implement advanced statistical models and machine learning algorithms.

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:

MS degree or PhD (preferred) in Statistics, Economics, Mathematics, or equivalent is required.

0-3 years industrial experience, preferably in software or system analytics, ecommerce, or financial services will be regarded favorably

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.

Knowledge of R, Python, Hadoop is preferred,

Excellent problem-solving skills and experience in deploying predictive models in production environments.

Superior communications skills, both verbal and written

Attention to detail and data accuracy.

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