Product Data Scientist, Geo Abuse and Risk

1 Month ago • 3-5 Years • Data Analyst

About the job

Job Description

As a Product Data Scientist, Geo Data Insights and Analytics (GDIA) Abuse and Risk, you will be working on problems that help us efficiently estimate rare event prevalence using a mix of sampling and advanced statistical techniques. You will focus on unearthing insights that help us keep maps safe from bad actors as well as how we can deliver a great contributor experience to good users. You will utilize a combination of tools including Large Language Models (LLMs), classical machine learning, user surveys, data pipelining, and more. You will work closely with Engineering, Operations and Product teams to track key metrics and the resulting impact. You will be performing large-scale data analysis, statistical modeling and inferential ML to identify opportunities for improvement and measure the impact of initiatives to make noticeable improvements based on impact and feedback. You will also be working on complex sampling algorithm development to model rare events and use stochastic methods in  understanding the real-world impacting our data moderation performance. You will be using tools such as Gen AI and similarity based clustering to remove bad content or help develop mitigation mechanisms.
Must have:
  • Master's degree in Statistics, Economics, Engineering, Mathematics, or a related quantitative field
  • 3 years of experience with statistical data analysis, data mining, and querying
  • 1 year of experience managing analytical projects
  • Excellent problem-solving and business judgment skills
  • Ability to articulate product questions, extract relevant data from large datasets using SQL
  • Leverage statistical analysis to derive actionable insights
  • Translate analysis results into actionable business recommendations
  • Excellent written and verbal communication skills
Good to have:
  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field
  • 5 years of work experience with analysis applications
  • Coding experience in Python, R, SQL
  • Experience with BigQuery
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Minimum qualifications:

  • Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience
  • 3 years of experience with statistical data analysis, data mining, and querying (e.g., SQL).
  • 1 year of experience managing analytical projects.

Preferred qualifications:

  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL).
  • Excellent problem-solving and business judgment skills with the ability to articulate product questions, extract relevant data from large datasets using SQL, BigQuery, or equivalent technologies, and leverage statistical analysis to derive actionable insights.
  • Ability to translate the analysis results into actionable business recommendations, with excellent written and verbal communication skills.

About the job

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.

As a Data Scientist, Product, with Geo Data Insights and Analytics (GDIA) Abuse and Risk, you will be working on problems that help us efficiently estimate rare event prevalence using a mix of sampling and advanced statistical techniques.

You will focus on unearthing insights that help us keep maps safe from bad actors as well as how we can deliver a great contributor experience to good users. You will utilize a combination of tools including Large Language Models (LLMs), classical machine learning, user surveys, data pipelining, and more. You will work closely with Engineering, Operations and Product teams to track key metrics and the resulting impact.

Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.

Responsibilities

  • Perform large-scale data analysis, statistical modeling and inferential ML to identify opportunities for improvement and measure the impact of initiatives to make noticeable improvements based on impact and feedback.
  • Work on complex sampling algorithm development to model rare events and use stochastic methods in  understanding the real-world impacting our data moderation performance.
  • Use tools such as Gen AI and similarity based clustering to remove bad content or help develop mitigation mechanisms.
  • Work with large data sets, build robust data pipelines, automate data extraction, and build monitoring/reporting dashboards for leadership.
  • Prioritize and communicate user needs, make recommendations and drive implementation for product or process changes. Identify and prioritize top issues and key growth opportunities.                                    
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About The Company

A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.

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