Senior Data Scientist, Research, App Safety Engineering
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Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field, or equivalent practical experience.
- 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:
- 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
About the job
Our team's mission is protecting billions of Android users from abusive apps, including malware, content abuse, impersonation, and behavioral abuse. Preventing abuse is fascinating technically and it features an adversarial scenario where we try to detect bad actors who try in turn to evade detection. Impact and success translates directly to keeping the Android ecosystem safe and protecting users from a variety of types of abuse.
As a Data Scientist on this team, you will work with multiple stakeholders across product, engineering and operation teams to conduct data research, build methodologies and dive deeply into production systems to drive key decisions and development. Analysis will span ecosystem impact and model efficacy. You will be responsible for translating data into meaningful recommendations and, where relevant, implementing process improvements. To succeed in this role, the Data Scientist should be someone who is highly quantitative, experienced in facilitating decisions through data, and capable of prioritizing requests from multiple stakeholders to have the most impact.
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.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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