Senior Data Scientist - App Safety Engineering
@ Google

New York, NY
$205,000
On Site
Full Time
Posted 23 days ago

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Job Details

Overview

The Senior Data Scientist - App Safety Engineering at Google focuses on protecting Android users from abusive apps, malware, and behavioral abuse. The role involves working with multiple stakeholders to build methodologies and improve detection of bad actors.

Minimum and Preferred Qualifications

Minimum: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering or related field with 5 years of relevant experience (or 3 years with a PhD).

Preferred: 8 years of experience (or 6 years with a PhD) using analytics, coding (Python, R, SQL), querying databases, or statistical analysis.

About the Job and Responsibilities

As part of the App Safety Engineering (ASE) team, you will:

  • Collaborate with cross-functional teams to clarify business or product questions.
  • Translate questions into tractable analysis, evaluation metrics, or mathematical models.
  • Utilize custom data infrastructure and existing models appropriately.
  • Design and evaluate models to solve defined problems in an adversarial setting.
  • Gather, extract, and compile data using tools such as SQL, Python, and R.

Additional Information

This role offers a competitive US base salary range of $166,000-$244,000 plus bonus, equity, and benefits. Google is an equal opportunity employer, committed to inclusion and diversity.

Key skills/competency

  • Data Science
  • Analytics
  • Python
  • SQL
  • R
  • Modeling
  • Statistical Analysis
  • Research
  • Engineering
  • App Safety

How to Get Hired at Google

🎯 Tips for Getting Hired

  • Customize your resume: Highlight analytics and model experience.
  • Showcase technical skills: Emphasize Python, R, and SQL proficiency.
  • Prepare examples: Detail your work in data research and modeling.
  • Research Google: Understand Google’s culture and recent initiatives.

📝 Interview Preparation Advice

Technical Preparation

Review Python, R, and SQL coding challenges.
Practice statistical modeling and data analysis techniques.
Study data infrastructure and extraction methods.
Review case studies on app safety analysis.

Behavioral Questions

Describe a challenging project in data research.
Explain collaboration with cross-functional teams.
Discuss adapting to project changes quickly.
Share a time you innovated process improvements.

Frequently Asked Questions