Google Meridian Specialist

Company Overview

Company overview not specified.

Job Summary

In this role, you’ll spearhead cross-channel measurement using Google Meridian, ensuring unified insights across digital and traditional media. Your analysis will shape smarter media allocation and optimize campaign performance in line with Crossmedia's values of trust, reason, and client satisfaction.

Responsibilities

• Build & Execute Crossmedia Models: Develop integrated marketing mix models with Google Meridian across channels like digital, TV, Out-Of-Home (OOH), social, and more.
• Aggregate & Interpret Multi-Platform Data: Integrate and analyze spend, performance, macro drivers, and query volume to derive actionable insights.
• Scenario Modeling & Forecasting: Simulate ROI and budget shift scenarios using Bayesian causal modeling to inform strategic media planning.
• Collaborate Across Teams: Partner with internal creatives, media strategists, and clients to align measurement insights with business goals.
• Maintain Data Transparency & Privacy: Ensure models use aggregated, privacy-compliant data consistent with Meridian’s open-source and transparent approach.

Qualifications

• Basic Qualifications:
  • 5+ years in marketing analytics, measurement, or media effectiveness roles.
  • Proficiency in Python or R for statistical modeling and data analysis.
  • Familiarity with both digital and traditional media channels.

Preferred Skills

• Hands-on experience with Google Meridian or other Marketing Mix Modeling (MMM) platforms.
• Skilled in Bayesian modeling, reach/frequency optimization, and budget allocation strategies.
• Strong communication skills—able to translate analytics into business strategy.

Experience

• Minimum of 5 years of relevant experience in marketing analytics or media effectiveness.

Environment

Typical work setting, location, and physical conditions not specified.

Salary

Salary information not specified.

Growth Opportunities

Career advancement opportunities not specified.

Benefits

Benefits offered not specified.