Business Data Scientist, YouTube Marketing Shopping

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.

Preferred qualifications:

• 5 years of experience in the consumer tech, media, or entertainment industry.
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
• Experience in causal inference techniques with a proven track record of applying them to solve business problems.
• Experience with advanced modeling techniques, including Marketing Mix Modeling (MMM), user LTV forecasting, and churn prediction and in e-commerce, retail analytics or two-sided marketplaces.
• Excellent communication and presentation skills, with a knack for distilling topics into simple, powerful messages.

About the job

In this role, you will join the YouTube Marketing Data Science, Infra and Analytics (DSIA), a analyst team that influences and informs YouTube’s marketing and products teams. You will work on projects that drive GTM and brand strategy for YouTube using data to ensure our marketing efforts are efficiently and effectively deployed.

As a Business Data Scientist on YouTube Shopping, you will be instrumental in optimizing marketing campaigns across the entire YouTube Shopping creator and viewer life-cycle. You will leverage your expertise in experimental design, data analysis, and machine learning to drive tangible improvements in creator engagement, viewer awareness, and overall platform efficacy.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we 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 $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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 benefits at Google.
The US base salary range for this full-time position is $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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 benefits at Google.

Responsibilities

• Partner with Growth Marketing and Product teams to analyze and optimize the end-to-end shopper journey, from acquiring new shoppers to driving repeat purchases.
• Develop user segmentation and propensity models to power personalized marketing campaigns, targeting shoppers with the right product at the right time.
• Collaborate with engineering and marketing to determine the signals we need to ensure we are connecting creators and viewers with the right offers at the right time.
• Develop and own the LTV models for YouTube shoppers, providing a critical input for long-term planning and investment.
• Design incentive programs experiments and optimize life-cycle communications with incentives.