Job Description

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:

• 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 delivering campaign analysis (through a series of experiments or an overarching campaign), fully automated analytics pipelines, audience segmentation or propensity modeling.
• Experience in engaging with external clients on measurement approaches, setting up experiments and reporting, with knowledge of R or Python for statistical analysis and SQL.
• Ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership with cross-functional stakeholders.

About the job

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.

The Platforms and Devices (P&D) Marketing analytics team works to deliver insights that drive better decisions. We leverage data analytics to unlock the potential of marketing at Google. The team is looking for a Data Scientist to drive the implementation of data science solutions, supporting the improvement of data pipelines, running geo-experiments, evaluating impact of marketing investments with external partners or helping the team develop evaluation metrics that provide insights to the business. This person will be passionate about marketing, has an innate curiosity about the consumers, and is eager to leverage advanced analytic capabilities to explain the impact from marketing actions. We are looking for a proactive leader to drive measurement, analysis and testing initiatives across a wide range of activities from brand media investment, partnerships, performance marketing, retail marketing and co-marketing with external partners.

In this role, you will manage measurement for Android partner marketing investments. You will leverage your data science skills to design experiments using internal data and while also guiding partners to set up effective experiments and measurement to help us evaluate impact of the marketing strategy.

Android is Google’s mobile operating system powering more than 3 billion devices worldwide. Android is about bringing computing to everyone in the world. We believe computing is a super power for good, enabling access to information, economic opportunity, productivity, connectivity between friends and family and more. We think everyone in the world should have access to the best computing has to offer. We provide the platform for original equipment manufacturers (OEMs) and developers to build compelling computing devices (smartphones, tablets, TVs, wearables, etc) that run the best apps/services for everyone in the world.

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

• Own data infrastructure. Manage and evolve the data infrastructure to generate deep user, tactic, and market insights, while scaling best practices across regional teams and the broader product portfolio.
  
• Drive causal experimentation. Work with external partners to design and consult on rigorous A/B experiments that isolate the causal impact of specific marketing actions.
  
• Narrate insights using data. Deliver customer-centric, data-driven insights that are grounded in data and clear frameworks, to understand the impact of full-funnel marketing strategies on the business.
  
• Enable effective decision making. Frame and solve ambiguous problems by scoping technical priorities and using statistical methods. Develop evaluation frameworks for making decisions, identify new metrics, and investigate anomalies.
  
• Innovate measurement. Build relationships with product teams and the broader Data Science community to develop new measurement methodologies, including AI tools to automate data solutions.