Data Scientist, Research, YouTube Trust and Safety
Job Summary
Job Description
This Data Scientist role at YouTube's Trust and Safety team focuses on evaluating and improving Google products. The position requires collaboration with engineers and analysts to solve product development challenges using scientific and statistical methods, with a focus on understanding user behavior. Responsibilities include translating business questions into analytical frameworks, designing and evaluating models, gathering and cleaning data using SQL, R, and Python, and ensuring data quality. The ideal candidate will have strong analytical skills and experience working with large datasets. Experience with Large Language Models or Generative AI is a plus. The role involves significant data analysis, model building, and cross-functional collaboration to improve YouTube's platform responsibility.
Must have:
- Master's degree in quantitative field
- 3+ years experience in analytics
- Proficiency in Python, R, SQL
- Data gathering, cleaning & analysis
- Model building and evaluation
Good to have:
- PhD in quantitative field
- 5+ years experience in analytics
- Experience with LLMs or Generative AI
- Experience with large-scale data infrastructure
Perks:
- Bonus
- Equity
- Benefits
4 skills required
Job Details
Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field 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 PhD degree.
Preferred qualifications:
- PhD in quantitative disciplines such as Statistics, Mathematics, Physics, Engineering, Computer Science, Operations Research, Economics or equivalent practical experience.
- 5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
- Experience with Large Language Models or Generative Artificial Intelligence evaluation.
- Interest and ability to support YouTube to become a responsible social media platform, with impact on our users and society.
About the job
As a Data Scientist, you will evaluate and improve Google's products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring scientific and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of the end user.The US base salary range for this full-time position is $127,000-$187,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .
Responsibilities
- Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
- Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
- Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
- Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Independently format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
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