Staff Data Scientist, Research

1 Month ago • 6-10 Years • Data Analyst • $177,000 PA - $266,000 PA

Job Summary

Job Description

As a Staff Data Scientist at Google, you'll evaluate and improve Google's products. You'll collaborate with engineers and analysts to solve a wide range of problems using scientific rigor and statistical methods. This role requires understanding end-user behavior and applying mathematical models to product creation, development, and improvement. Responsibilities include collaborating with stakeholders to define business questions, translating them into tractable analyses, designing and evaluating models, gathering and compiling data, and ensuring data quality. You'll use tools like SQL, R, and Python to work with various data sources. This role demands expertise in statistical analysis and a proven ability to apply analytics to solve complex business problems.
Must have:
  • Master's degree in quantitative field
  • 8 years of experience (or 6 with PhD)
  • Proficiency in Python, R, SQL
  • Strong analytical and problem-solving skills
  • Experience with large datasets
Good to have:
  • 10 years of experience (or 8 with PhD)
  • Experience with Google's data infrastructure
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

Minimum qualifications:

  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • 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.

Preferred qualifications:

  • 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.

About the job

Google is and always will be an engineering company. 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 millions, if not billions, of users. At Google, data scientists not only revolutionize search, they routinely work on massive 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. As a Data Scientist, you will evaluate and improve Google's products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of the end user.

The US base salary range for this full-time position is $177,000-$266,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .

Responsibilities

  • Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  • Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
  • Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
  • Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Independently format, re-structure, and/or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

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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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