About the Job

• Develop safety solutions for AI products across Google by leveraging Machine Learning and AI techniques.

• Apply statistical and data science methods to examine Google's protection measures, uncover potential shortcomings, and develop insights for continuous security enhancement.

• Drive business outcomes by crafting data stories for a variety of stakeholders, including executive leadership.

• Develop automated data pipelines and self-service dashboards to provide timely insights.

• Work with sensitive content, situations, you will be exposed to graphic, controversial, or upsetting topics or content.

Responsibilities

• Develop safety solutions for AI products across Google by leveraging Machine Learning and AI techniques.

• Apply statistical and data science methods to examine Google's protection measures, uncover potential shortcomings, and develop insights for continuous security enhancement.

• Drive business outcomes by crafting data stories for a variety of stakeholders, including executive leadership.

• Develop automated data pipelines and self-service dashboards to provide timely insights.

• Work with sensitive content, situations, you will be exposed to graphic, controversial, or upsetting topics or content.

Minimum Qualifications

• Bachelor's degree or equivalent practical experience.

• 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.

• 2 years of experience managing projects and defining project scope, goals, and deliverables.

Preferred Qualifications

• Master's degree or PhD in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Physics, Operations Research, etc).

• 3 years of experience in a data analysis or data science setting and in abuse and fraud disciplines.

• Experience in programming languages (e.g., Python, R, Julia), database languages (e.g. SQL) and scripting languages (e.g., C/C++, Python, Java).

• Experience with prompt engineering and fine-tuning LLMs.

• Experience applying machine learning techniques to the datasets.

• Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.