Analytical Performance Lead (English, French)

Being an Analyst at Google is about much more than simply crunching numbers – it’s about finding compelling insights within data and using your exceptional business and communication skills to translate those insights into action. As one of the masterminds behind our strategic planning, forecasting and analysis, you’ll spend your time digging into big, complex data sets. The data will not remain inert in your hands, however, since you’ll use your critical thinking, problem solving and communication skills to influence and drive thoughtful and well-informed decision making with our most senior business leaders within the organization, and potentially some of our biggest clients.

As an Analytical Performance Lead in LCS France, you will serve as the investigative and technical engine of the Performance Leads team. While contributing directly to our core mission—growing Performance Ads business through data-backed Growth Pitches, Demand-Led Growth, AI Readiness, and Future of Search/Search Compete initiatives—you will hold a specialized Analytical Consultant mandate.
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.

France: €68000 - €69500 (EUR) + 35% bonus target + equity + benefits

Learn more about benefits at Google (https://www.google.com/about/careers/applications/benefits/).

Minimum qualifications:

- Bachelor’s degree in a quantitative field (e.g., Data Science, Engineering, Statistics, Economics, Computer Science, Business Analytics), or equivalent practical experience.

- 2 years of experience in data analytics, business intelligence, marketing science, quantitative consulting, or digital performance analytics.

- Ability to communicate in English and French fluently to collaborate with local sales teams, French advertisers, and global gTech stakeholders.

Preferred qualifications:

- Experience with programming or scripting languages (e.g., Python or R) for statistical modeling (diminishing returns/performance curves, forecasting), workflow automation, and AI-powered tool development.

- Experience collaborating with technical cross-functional teams to scope, prioritize, and scale products and reporting infrastructure.

- Strong technical proficiency in SQL (querying complex relational databases, writing optimized queries, and materializing tables) and data visualization/BI platforms (e.g., Looker Studio, Tableau, or Power BI).

- Demonstrated ability to translate complex technical analyses and search behavior data into clear, persuasive commercial narratives for non-technical audiences.

- Analyze large, complex datasets through advanced quantitative modeling (e.g., performance curves, auction and market-share opportunity sizing, ROI/margin forecasts) and translate insights into compelling budget recommendations.

- Serve as the primary Point of Contact (POC) and interface between LCS France and the gTech Insights team as well as EMEA GTM Tools and Insights leads.

- Act as the investigative gatekeeper for custom dashboard and insight requests across LCS France: assess incoming requests against expected commercial impact, prioritize the roadmap, and ensure rapid execution on high-value deliverables.

- Partner with gTech Insights and fellow Performance Leads to upgrade and scale quantitative pitch methodologies (leveraging SQL, scripting: Python/R/Apps Script).

- Develop compelling narratives to deliver scalable insights across a broad customer base, capitalizing on key seasonal moments and industry trends (e.g., Retail advertisers).