Data Scientist II, Product

1 week ago


Mountain View, United States Google Full time

Minimum qualifications:

  1. Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  2. 2 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 1 year of work experience with a Master's degree).

Preferred qualifications:

  1. Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  2. 3 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL).

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.

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. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.

Responsibilities:

  1. Perform analysis utilizing relevant tools (e.g. SQL, R, Python). Apply standard/common tools, resources, and processes to defined problems and for moderately difficult projects, execute analytical tasks with guidance.
  2. Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and validate data to ensure quality.
  3. Leverage a foundational understanding of broader business priorities and analytical techniques.
  4. Select appropriate approaches from clear options to address technical challenges.
  5. Develop working relationships outside of the team to contribute to cross-project collaborations and better understand data or products.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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