Technical Operations Intern – Analytical Operations

Job Description

Technical Digital Marketing Intern | Eulerity

The Tone:
This is an internship at Eulerity, located in New York, NY. Eulerity builds an AI-native marketing automation platform that autonomously manages paid advertising, social media, listings, reputation, and call tracking for thousands of enterprise franchises and SMB networks. This role is crucial for the Technical Operations team, serving as the analytical engine that ensures the sharp execution and performance of marketing campaigns. It is a highly analytical position focused on data-driven insights, not traditional marketing tasks.

The TL;DR
• Role: Internship
• Type: Summer 2026, minimum 20 hours per week, flexible schedule, potential to extend
• Location: Hybrid, New York, NY
• Pay: $16–$18 hourly
• Team: Technical Operations team, working directly with Technical Account Management and Analytics teams
• Mission: To diagnose campaign performance, build analytical tools, and identify data patterns that drive effective marketing campaign execution.
• Tech Stack: Google Ads, Meta, LinkedIn, Excel, Sheets, SQL, Python, JavaScript, AI tooling

What You’ll Actually Do
• Diagnose: Diagnose why specific campaigns are underperforming and propose fixes grounded in the data.
• Build: Build and refine Excel and Sheets models that our account teams use to make decisions.
• Audit: Audit campaigns at scale, often across hundreds of locations for a single brand, and surface patterns no one else has noticed.
• Analyze: Pull, clean, and analyze performance data from Google Ads, Meta, LinkedIn, and our internal platform.
• Operationalize: Help operationalize new analytical workflows, including ones we are building on top of AI tooling.
• Contribute: Contribute to internal projects that make our team faster and smarter.

The Must-Haves
• Background: Current student or recent graduate, ideally with coursework in quantitative fields such as Economics, Statistics, Computer Science, Engineering, Math, or Finance.
• Experience: Comfort with building models in Excel to understand complex information. Experience using AI tools aggressively and intelligently as a daily part of work.
• Skills: Strong proficiency in Excel, including pivot tables, lookups, conditional logic, and building models from scratch. Basic code literacy, with the ability to read and roughly understand SQL, Python, or JavaScript. Sharp written communication skills to explain complex analysis clearly and concisely. Detail-oriented and self-directed, catching details others miss.