Data Scientist

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree in Statistics, Computer Science, Mathematics, or a related

field and 2 years of experience in the job offered or in a Data

Scientist-related occupation.

• Position requires 2 years of experience in the following: SQL for data

extraction and manipulation; Data pipeline creation for data engineering;

Python or R for statistical analysis and problem-solving; Applying

statistical methods including t-tests and descriptive statistics; and

Performing root cause analysis using quantitative methods.

ABOUT THE JOB:

Google Cloud accelerates every organization’s ability to digitally transform its

business and industry. We deliver enterprise-grade solutions that leverage

Google’s cutting-edge technology, and tools that help developers build more

sustainably. Customers in more than 200 countries and territories turn to Google

Cloud as their trusted partner to enable growth and solve their most critical

business problems.

The US base salary range for this full-time position is $138,000 - $198,000 +

15% bonus target + equity + benefits determined by role, level, and location.

Individual pay is determined by additional factors, including job-related

skills, experience, and relevant education or training. Learn more about

benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

Position reports to the Google office & may allow for a hybrid schedule as per

Google policy.

RESPONSIBILITIES:

• Manage the end-to-end data lifecycle by gathering, extracting, and compiling

data from various sources using tools like SQL, R, or Python while ensuring

data quality and security.

• Conduct in-depth analysis and design statistical models to interpret complex

datasets, formulate conclusions, and iteratively build prototypes that

provide insights at scale.

• Collaborate with stakeholders to define and refine key business questions,

developing an analytical roadmap and methodology to address product or

business challenges effectively.

• Translate complex analytical findings into actionable insights and strategic

recommendations to influence product development decisions and long-term

business strategy.

• Present key performance indicators and analytical results to support business

reviews and communicate opportunities to cross-functional leadership teams.

Develop comprehensive knowledge of internal data structures and advocate for

infrastructure improvements to enhance data quality and processing

capabilities for future analyses.