Strategic Data Scientist, ML & Ops for Product Analytics

Google; Dublin; On-site; EUR 90,000 - 92,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Google Dublin is seeking a Business Data Scientist to join Product Services Analytics (PSA). You will drive data-backed decision making across Google's operations, blending data science with product and engineering collaboration to scale impactful ML/AI solutions.

You will mentor others, design robust data pipelines, and translate analytical findings into strategic recommendations for executives, while aligning with global product objectives.

Qualifications

• Master's degree in a quantitative field such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
• Experience with Machine Learning (ML) models or Artificial Intelligence.

Responsibilities

• Translate ambiguous business and operational challenges into scalable investigative solutions, models, and actionable insights.
• Lead project work and mentor team members in designing and deploying data science models, ML/AI solutions, robust data pipelines, and evaluation frameworks.
• Build and implement reusable, scalable investigative tools and automated solutions that optimize the operational processes.
• Collaborate with engineering partners to write robust code and implement tools that improve troubleshooting efficiency, operational workflows, and the end-user experience.
• Manage cross-functional stakeholder expectations, communicating complex technical findings and data insights clearly to both technical and non-technical audiences to drive business decisions.

Education

Master's degree

Tools

Python

R

SQL

Job description

Google Dublin is seeking a Business Data Scientist to join Product Services Analytics (PSA). You will drive data-backed decision making across Google's operations, blending data science with product and engineering collaboration to scale impactful ML/AI solutions.

You will mentor others, design robust data pipelines, and translate analytical findings into strategic recommendations for executives, while aligning with global product objectives.