Data Scientist, Research Intern, PhD, Summer 2027

Socket.dev; Mountain View (CA); On-site; USD 118,000 - 157,000; Full time

Job summary

Google is seeking a Data Scientist - Research in Mountain View to process, analyze, and interpret large datasets to shape Google's business and technical strategies. You will identify opportunities for efficiency and impact by applying statistical methods and collaborating with diverse teams.

You will work with engineers, product managers, sales and marketing to implement findings and adjust practices accordingly. Demonstrated leadership and willingness to learn are valued as essential traits.

Qualifications

• PhD student or candidate in a quantitative field with strong statistical training.
• Experience applying linear models, multivariate analysis, stochastic processes, and sampling methods.
• Proficient in data analysis with scripting languages (R or Python).

Responsibilities

• Work with large, complex data sets and perform advanced analyses.
• Build and prototype analysis pipelines to deliver insights at scale.
• Collaborate cross-functionally with engineers, PMs, sales, and marketing.
• Present findings and recommendations to stakeholders with clear visualizations.
• Research and develop methods to improve analysis quality and product decisions.

Skills

PhD in quantitative discipline

Statistical methods

Data analysis

R/Python

Education

PhD student in quantitative field

Tools

SAS

Job description

Minimum qualifications:

• Currently pursuing a PhD degree in a quantitative discipline (e.g., statistics, biostatistics, physics, applied mathematics, operations research, economics).
  
• Experience with statistical methods (linear models, multivariate analysis, stochastic processes, sampling methods, etc.).
  
• Experience with data analysis.
• Experience using R or Python and technology to work with datasets such as scripting or statistical software (R, SAS, etc.).
  

Preferred qualifications:

• Currently attending a degree program in the US and available to work full time for 12 weeks outside of university term time.
  
• In their penultimate academic year or returning to a degree program after completion of the internship.
  
• Ability to draw conclusions from data and recommend actions.
• Ability to take on a leadership role and take initiative.
  
• Interest in learning new techniques.
  

About the job:

At Google, data drives all of our decision-making. In the Data Scientist - Research role, you will 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 will 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. You will 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.

Google is and always will be an engineering company. We hire people with a broad set of technical skills who are ready to address some of technology's greatest challenges and make an impact on millions, if not billions, of users. At Google, engineers 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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $118000 - $157000 (USD) + 0% bonus target

Learn more about benefits at Google.

Responsibilities:

• Work with large complex data sets, solve difficult non-routine analysis problems, and apply advanced analytical methods. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
• Build and prototype analysis pipelines iteratively to provide insights at scale. Develop a comprehensive understanding of Google data structures and metrics, advocating for changes.
• Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities, design and assess improvements to Google products.
• Make business recommendations (e.g., cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
• Research and develop analysis, forecasting, and optimization methods to improve the quality of Google's user products.