Data Scientist, Research, App Safety Engineering

20 Hours 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 production methodologies, and drive key ASE decisions and development. Your analysis will encompass ecosystem impact and model efficacy, translating data into actionable recommendations and process improvements. You'll work with large, complex datasets, solving challenging analytical problems using advanced quantitative methods. Responsibilities include defining objectives and metrics with stakeholders, developing and evolving methodologies, understanding production systems, advocating for necessary changes, and building data-driven solutions to enhance efficacy. You'll need expertise in data gathering, processing, analysis, model development and evaluation, and effectively communicating results to various business partners.
Must have:
  • Master's degree in relevant quantitative field
  • 5+ years experience using analytics to solve problems
  • Proficiency in Python, R, SQL
  • Experience with database querying and statistical analysis
  • Data analysis & problem-solving skills
Good to have:
  • 8+ years experience
  • Experience articulating business questions and using statistical techniques

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 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 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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