Cloud Data Scientist - ML, A/B Testing & Big Data

eBay; Dublin; On-site; EUR 90,000 - 120,000; Full time

Job summary

eBay is seeking a Data Scientist in Dublin to improve decision-making through advanced analytics. You will build and evaluate models, apply ML techniques, and contribute to bot detection and customer profiling initiatives. Strong Python or R skills and SQL proficiency are essential, with experience in Hadoop/Spark in cloud environments.

The role focuses on experimentation, causal inference, and collaboration with cross-functional teams to deliver scalable data solutions.

Qualifications

• 5+ years of relevant experience with a master’s degree or Ph.D. in Computer Science or another quantitative field.
• Experience building statistical or ML models and evaluating model performance.
• Proficiency in Python or R and ML libraries such as scikit-learn or GBM.
• Advanced SQL skills and experience optimizing large-scale queries.
• Experience with Hadoop and Spark in cloud environments.

Responsibilities

• Contribute to complex data science projects from analysis through model development and evaluation.
• Develop and implement advanced statistical models and ML algorithms to address business challenges.
• Support experimentation and causal inference initiatives including A/B and multivariate testing.
• Use advanced SQL to work with large-scale datasets and optimize big data queries.
• Collaborate with cross-functional teams to define requirements and develop data solutions.

Education

Master's degree or PhD in Computer Science or related quantitative field

Tools

Hadoop

Spark

scikit-learn

GBM

Python

R

SQL

Job description

eBay is seeking a Data Scientist in Dublin to improve decision-making through advanced analytics. You will build and evaluate models, apply ML techniques, and contribute to bot detection and customer profiling initiatives. Strong Python or R skills and SQL proficiency are essential, with experience in Hadoop/Spark in cloud environments.

The role focuses on experimentation, causal inference, and collaboration with cross-functional teams to deliver scalable data solutions.