About the job

g Tech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within Google to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with Google and we remain a trusted partner.

In this role, you will be responsible for applying best data science practices to solve our advertising customers marketing issues. You will be passionate about bringing the best of Google’s Machine learning (ML) capabilities to build solutions that address our customer's problem-space.

You will be responsible for executing on g Tech’s strategy and goal to deliver applied data science to Google's largest Ads customers.

Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.

Responsibilities

• Collaborate with internal and external stakeholders to unpack their issues and identify the best statistical techniques that can solve the issue; collaborate with colleagues on the development of end-to-end modeling framework.

• Own the full data science lifecycle from raw data extraction and model development to delivering the final solution. Ensure the technical excellence of the math and the business relevance of the output.

• Transform model results into "so-what" insights. Co-present findings to clients and work alongside them to ensure recommendations are integrated into their actual business processes.

• Contribute to the development of standardized, scalable modeling frameworks. Collaborate with DS peers to ensure our solutions aren't just one-offs, but can be scaled across multiple client engagements.

Minimum qualifications

• Bachelor's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.

• 1 year of experience in a data science field.

Preferred qualifications

• 2 years of experience using Python, SQL to solve messy, open-ended business problems.

• Experience taking Machine Learning (ML) insights directly to customers or stakeholders including initial problem scoping and model selection to interpretation and driving business action.

• Understanding of statistical models and their application in a commercial context.

• Understanding of statistical algorithms typically used in marketing analytics e.g. experimentation (A/B testing), causal inference, and attribution modeling.