Artificial Intelligence Safety Data Scientist
Job Overview
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Job Description
Artificial Intelligence Safety Data Scientist
Trust & Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, you're a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety.
The Artificial Intelligence (AI) Safety Protections team within Trust and Safety develops and implements AI/Large Language Model (LLM)-powered solutions to ensure the safety of Generative AI foundational models.
In this role, you will be mitigating risks associated with Generative AI, and addressing safety with LLM/AI technology (e.g., imminent threat, child safety) as the community contribution. You will have the opportunity to apply the latest advancements in AI/LLM and work with teams developing AI technologies. At Google we work hard to earn our users’ trust every day. Trust & Safety is Google’s team of abuse fighting and user trust experts working daily to make the internet a safer place. We partner with teams across Google to deliver bold solutions in abuse areas such as malware, spam and account hijacking. A team of Analysts, Policy Specialists, Engineers, and Program Managers, we work to reduce risk and fight abuse across all of Google’s products, protecting our users, advertisers, and publishers across the globe in over 40 languages.
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 in managing projects and defining project scope, goals, and deliverables.
Preferred Qualifications
- Master’s degree or PhD in Computer Science, Statistics, Mathematics, Operations Research, or in a related quantitative field.
- 3 years of experience in data analysis or data science environment.
- Experience in abuse and fraud environments, with web security, content moderation and threat analysis.
- Experience with programming languages (e.g., Python, R, Julia, Java, C or C++), database languages (e.g., SQL).
- Experience in applying machine learning techniques to datasets.
- Excellent problem-solving and thinking skills, with attention to detail in a changing environment.
Responsibilities
- Develop safety solutions for AI products across Google by leveraging advanced machine learning and AI techniques.
- Apply statistical and data science methods to examine Google's protection measures, uncover shortcomings, and develop insights for security enhancement.
- Drive business outcomes by crafting data stories for multiple stakeholders, including executive leadership.
- Develop automated data pipelines and self-service dashboards to provide insights.
- Work with sensitive content or situations which may be exposed to graphic, controversial or upsetting topics or content.
Key skills/competency
- AI Safety
- Generative AI
- Large Language Models (LLM)
- Data Analysis
- Machine Learning
- Statistical Methods
- Python
- SQL
- Project Management
- Trust & Safety
How to Get Hired at Google
- Research Google's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight AI safety, data science, machine learning, and project management experience for Google.
- Showcase technical prowess: Emphasize strong skills in Python, SQL, ML, and Generative AI applications.
- Prepare for behavioral questions: Focus on problem-solving, collaboration, ethical considerations, and impact on user safety.
- Network strategically: Connect with Google employees in Trust & Safety or AI teams on LinkedIn for insights.
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