Marketing Science Lead

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in media analytics, advertising sales, digital media and marketing, consulting, or financial analysis.

Preferred qualifications:

• Expertise in first-party data strategies, customer data infrastructures (CDP/CRM), and Google’s measurement ecosystem - including Google Analytics, Google Ads, tagging systems (gTag, GTM, server-side GTM), and APIs (e.g., Data Manager API, Google Cloud integrations).
• Knowledge of online (Search, Display, Video/CTV) and offline (TV, OOH) advertising channels, brand analysis techniques, and the application of modern AI-powered marketing tools.
• Understanding of brand and performance measurement frameworks, with proven experience executing marketing experiments, incrementality testing, causal impact, (MMM/Meridian), and Multi-Touch Attribution (MTA).
• Ability to analyse datasets, apply statistical and financial modeling, and translate quantitative outputs into commercial insights.

About the job:

As a Data, Measurement and Analytics (DM&A) Specialist, you will act as an advisor to Google’s largest and most sophisticated advertisers. You will lead the measurement and experimentation strategy, using insights to solve business issues and unlock new avenues for growth during a pivotal moment of industry transformation. Working at the intersection of media, technology, and data science, you will partner with our clients to guide their measurement maturity and support their business goals.

You will be a collaborative problem-solver who navigates ambiguity and possesses business acumen. You will build trusted relationships with key decision-makers, including executive leaders across marketing, analytics, and strategy, and seamlessly partner with Google's sales and product teams. By translating datasets into compelling narratives, you will influence critical business decisions and motivate organizational change. With a background in advanced marketing analytics, you will be an expert in demonstrating media value through incrementality, Marketing Mix Models (MMM), attribution, and AI-driven solutions. You will empower investigative clients to modernize their measurement infrastructure by integrating first-party data and adopting privacy-safe best practices, ultimately ensuring their media investments deliver, real-world success.

Google's Large Customer Sales (LCS) teams are strategic partners and industry thought leaders to the world's leading brands and agencies. We continuously challenge how customers think about their business and how Google can support growth. We focus on helping these players navigate profound industry shifts and drive outsized business performance by competitively selling Google's full suite of advertising solutions across Search, YouTube, Measurement, and more. As a member of our LCS team, you'll have the unique opportunity to sell at the forefront of technology, collaborating with executives, influencing market-shaping strategies, and delivering tangible results that significantly impact major global businesses and drive the growth of Google.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Canada: $138000 - $141000 (CAD) + 40% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

• Understand and pitch privacy-durable data foundations for clients by driving the implementation of Google’s tagging infrastructure (gTag, GTM, server-side GTM) and advanced first-party data solutions (Data Manager API, Google Cloud integrations) to ensure resilient signal capture.
• Develop, own, and execute comprehensive joint measurement plans for advertisers and agencies, integrating data foundations, incrementality experiments, Marketing Mix Modeling (MMM), full-funnel measurement, and attribution frameworks to prove media value.
• Act as a trusted technical advisor to decision-makers, test the status quo, build executive partnerships, and deliver data stories.
• Lead the business-cycle for prioritized data and measurement opportunities across Google Ads and Google Marketing Platform products.
• Apply data science, causal inference, and statistical modeling techniques to design incrementality experiments, optimize Marketing Mix Modeling (MMM) data inputs, and help clients navigate changing industry privacy standards.