Business Data Scientist, Ads Marketing Analytics

Google • Mountain View, CA

3h • $141,000 - $202,000

About The Position

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

As a Data Scientist on the Ads Marketing data science team, you will perform deep data analytics, drive initiatives in experimentation, measurement and advance machine learning modeling capability to support global marketing programs. In collaboration with a multidisciplinary team of marketing, product management, data scientists and engineers, you will tap into the underlying data, develop and align on key metrics/methodologies and generate insights that enable marketers to develop powerful, highly effective marketing programs. You will leverage core Data Science expertise to design, prototype and build out analysis pipelines to support initiatives and Marketing campaigns, perform analytics, design and execute on experimentation, and conduct incrementality measurement analysis to inform on key decisions of the marketing programs across the entire Ads Marketing space, from acquisition, onboarding and growth.The US base salary range for this full-time position is $141,000-$202,000 + 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 [https://careers.google.com/benefits/].

Requirements

• 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.

Nice To Haves

• PhD degree in Statistics or related quantitative discipline.
• 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 controlled experiment design and causal inference methods.

Responsibilities

• Work with large data sets. Solve analysis problems, applying advanced investigative methods (such as statistical and machine learning models) as needed. Conduct analysis that includes problem formulation, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
• Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of Ads marketing programs.
• Build and prototype analysis pipelines iteratively to provide insights. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed.
• Interact cross-functionally, making 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.
• Develop and automate reports, iteratively build and prototype dashboards to provide insights, solving for business priorities.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level