Data Scientist, Research, App Safety Engineering

1 Month ago • 3-8 Years • Data Analyst

Job Summary

Job Description

As a Data Scientist on Google's App Safety Engineering (ASE) team, you'll collaborate with product, engineering, and operations teams to conduct data research, build methodologies, and improve production systems. Your analysis will cover ecosystem impact and model efficacy, translating data into recommendations and process improvements. Responsibilities include working with large datasets, solving complex analysis problems using advanced quantitative methods, collaborating with stakeholders, defining metrics, and developing methodologies. You'll need experience in data gathering, processing, analysis, model development, and communication. You'll also advocate for system changes and build data-driven solutions to enhance efficacy. The goal is to protect billions of Android users from abusive apps.
Must have:
  • Master's degree in quantitative field
  • 5+ years experience (or 3 with PhD)
  • Proficient in Python, R, SQL
  • Data analysis & statistical modeling
  • Excellent communication skills
Good to have:
  • 8+ years experience (or 6 with PhD)
  • Experience with large-scale datasets
  • Experience in Android ecosystem

Job Details

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:

  • 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.
  • Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data.

About the job

At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution.

Our team's mission is protecting billions of Android users from abusive apps, including malware, content abuse, impersonation, and behavioral abuse. 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 App Safety Engineering (ASE) 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 ASE 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. You will have experience in facilitating decisions through data, and prioritize requests from multiple stakeholders to have the most impact.

Responsibilities

  • Work with large, complex datasets; solve difficult, non-routine analysis problems, applying advanced quantitative methods as needed.
  • Conduct analysis that includes data gathering and requirements specification, processing, analysis, model development and evaluation, as well as written and verbal delivery of results to business partners.
  • Collaborate closely with stakeholders in Product Management, Engineering and Operation teams to define relevant questions, objectives and metrics, identify and implement quantitative methods to answer those questions.
  • Develop, own and evolve methodologies and frameworks providing a source of truth measures for the organization.
  • Establish comprehensive understanding of the production systems, advocate for changes where needed for product development, and build data driven solutions to faciliate the efficacy improvement.

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