Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.
Preferred qualifications:
- PhD degree in a quantitative discipline (e.g., Statistics, Mathematics, Physics, Engineering, Computer Science, Operations Research, Economics).
- 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
- 1 year of experience in leadership, mentoring, or management.
- Experience leading complex projects, with multiple cross-functional stakeholders and changing priorities.
As a Data Scientist Tech Lead, you will be focused on mitigating abuse like scams, misinformation, and harassment. You will have the opportunity to leverage deep mathematical and statistical expertise and work with Machine Learning (ML) engineers to develop and apply machine learning techniques, including enhancing ML model, optimizing data sampling for fine tuning large multimodal AI models, and contributing to the development of advanced Large Language Models (LLM )based content moderation tools. You will guide and mentor other data scientists and engineers working in this critical space. You will bring novel methodologies to the team, driving innovation in how we detect and address emerging threats
The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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
benefits at Google.
- 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 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). Format, re-structure, and validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
