Marketing Science Lead

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.

Responsibilities

• Define and execute strategic client learning agendas and experimentation roadmaps—using A/B testing, Geo-experiments and other Google proprietary methods—to quantify and unlock business growth generated by investments from Google Ads.
  
• Distill complex analytical and experimental findings into highly actionable, non-technical business recommendations and executive-ready presentations that marketing leaders can immediately deploy to drive revenue.
  
• Act as trusted consultant to help advertisers audit and modernize their data infrastructure, safeguarding their long-term ad performance and automated bidding efficiency against privacy changes and signal loss.
• Advise advertisers on budget allocation and testing feasibility, while leading executive reviews and workshops to build investment confidence across sales teams and agency partners.

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.
  
• Experience working with partners to identify technical challenges and opportunities, and selling AdTech/MarTech solutions.
  

Preferred qualifications:

• MBA or Master's degree in quantitative field like Data Analytics, Economics.
• Experience in quantifying ROI and improving ROI of ads spends through test and learn approach in one of the following: experimental methods (e.g., A/B testing, Geo experiments, user lift experiments), Advanced attribution (e.g., SKAN, MTA), statistical methods (e.g., causal inference, MMM, Statistical MTA).
• Experience managing and influencing senior stakeholder relationships on recommending data driven ways to improve product and customer strategy to drive business outcomes.
• Experience with incrementality testing, causal impact analysis, MMM, and MTA.
• Understanding of brand and performance measurement.