Growth-Driven Paid Search & Social Marketer

U.S. News & World Report; Washington (District of Columbia); Hybrid; USD 70,000 - 95,000; Full time

Job summary

U.S. News & World Report is seeking a hands-on Paid Search & Social Marketing Specialist to support a cross-vertical team. You will drive high-intent audience growth, engagement, and lead generation with deep platform familiarity and rigorous A/B testing.

The role focuses on execution, optimization, and scaling across SEM and Paid Social, with a strong emphasis on building out an A/B testing program and improving attribution models in collaboration with data and UX teams.

Qualifications

• Minimum 3 years’ hands-on performance marketing experience.
• Experience with paid search and paid social channels.
• Strong Excel/Sheets and GA4 analytics.
• Bachelor's degree in Marketing, Economics, Statistics, Communications, or related field.

Responsibilities

• Build, launch, and manage daily campaigns across search engines and major paid social platforms.
• Integrate paid search and paid social strategies with partner performance and data.
• Develop end-to-end A/B testing pipelines for rapid learning and optimization.
• Collaborate with Data Science, UX, and Content teams on attribution and lead quality.
• Monitor budgets and bidding strategies to meet acquisition targets.

Skills

Performance marketing

Paid search

Paid social

Excel / Sheets

GA4

Looker Studio

Landing page optimization

Copywriting

UX understanding

Education

Bachelor's degree in Marketing, Economics, Statistics, Communications, or related field

Tools

Google Ads

Meta Ads Manager

LinkedIn Campaign Manager

TikTok Ads

Job description

U.S. News & World Report is seeking a hands-on Paid Search & Social Marketing Specialist to support a cross-vertical team. You will drive high-intent audience growth, engagement, and lead generation with deep platform familiarity and rigorous A/B testing.

The role focuses on execution, optimization, and scaling across SEM and Paid Social, with a strong emphasis on building out an A/B testing program and improving attribution models in collaboration with data and UX teams.