Join our Large Customer Sales team as an Analytics Lead and become the vital link between data insights and impactful business decisions. You'll partner with leading advertisers, guiding them through the complexities of digital measurement to enhance their return on investment. This role offers the opportunity to design experiments, implement advanced modeling, and demonstrate the true value of advertising spend, shaping the future of the advertising industry through data storytelling.

As an Analytics Lead, you will manage strategic client relationships by developing measurement strategies and learning agendas that drive improved business outcomes. You will navigate a complex network of agencies, brands, and internal teams to foster the adoption of Google's measurement objectives. Key duties include designing and executing in-depth custom analyses and ad-effectiveness studies to quantify marketing strategy impact across various platforms. You will also collaborate with Product and R&D teams on future Google tools, leading client pilots for new products and educating the industry on Google's measurement approach. Your work will involve authoring white papers on performance marketing techniques and translating complex technical findings into actionable insights for diverse audiences.

A Bachelor's degree or equivalent practical experience is required, alongside a minimum of 5 years of experience in media analytics, advertising sales, digital media and marketing, consulting, or financial analysis. Essential skills include experience with measurement techniques such as A/B Testing, Causal Inference, Randomized Controlled Trials (RCTs), Geo experiments, Marketing Mix Modeling (MMM), or Multi-Touch Attribution (MTA). Proficiency in data querying and analysis using SQL, Python, or R is also a necessity. Preferred qualifications include 1 year of experience with marketing measurement, attribution techniques, and Google advertising products, as well as client-facing experience with influencing capabilities. Familiarity with SQL, databases, and basic automation techniques, along with the ability to analyze large datasets and communicate findings effectively, are highly valued.