Business and Marketing Data Scientist

About the job

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.

The US base salary range for this full-time position is $194,850 to $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.

Minimum qualifications:

• Bachelor’s degree in Data Science, Statistics, Applied Mathematics, Computer Science, or a related field and 6 years of progressive, post-baccalaureate experience in the job offered or in a Business and Marketing Data Scientist-related occupation.
• Alternatively, will accept a Master’s degree in Data Science, Statistics, Applied Mathematics, Computer Science, or a related field, and 4 years of experience in the job offered or in a Business and Marketing Data Scientist-related occupation.
• Position requires 4 years of experience in the following: (1) Data gathering, extraction, and compilation using SQL, R, or Python; (2) Formatting, re-structuring, and validating data to ensure quality standards; (3) Data formulation and interpretation by synthesizing multi-source data; (4) Defining data requirements, data sources, and data formats; and (5) Defining measurable business objectives and mapping them to scalable data solutions.

Responsibilities

• Collaborate with stakeholders to identify and refine complex business questions, translating them into tractable analysis and statistical models
• Drive the gathering, extraction, and compilation of data across diverse sources using tools like SQL, R, and Python, ensuring quality and security
• Formulate and interpret data to reach specific conclusions and recommend next steps with minimal guidance, providing feedback on analyses from others
• Develop and define key metrics to track and evaluate solution implementation and deployment, identifying product gaps through metric analysis
• Create and automate dashboards and reporting tools that generate insights for internal teams, guide product decisions, and support OKR identification & Write, validate, and document high-quality solution code integrated with production systems while creating repeatable solutions and best practices for others