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Junior

AI-Powered Growth Intelligence Associate

Confirmed live in the last 24 hours

Groupon

Groupon

Chicago (35 W. Wacker Dr.); Remote - United States
Hybrid
Posted April 22, 2026

Job Description

Groupon is a marketplace where customers discover new experiences and services everyday and local businesses thrive. To date we have worked with over a million merchant partners worldwide, connecting over 16 million customers with deals across various categories. In a world often dominated by e-commerce giants, we stand out as one of the few platforms uniquely committed to helping local businesses succeed on a performance basis.

Groupon is on a radical journey to transform our business with relentless pursuit of results. Even with thousands of employees spread across multiple continents, we still maintain a culture that inspires innovation, rewards risk-taking and celebrates success. The impact here can be immediate due to our scale and the speed of our transformation. We're a "best of both worlds" kind of company. We're big enough to have the resources and scale, but small enough that a single person has a surprising amount of autonomy and can make a meaningful impact.

About the Role:

Groupon is rebuilding how it sells — from the ground up, with AI. The vehicle is Project Foundry: a production fleet of AI agents designed to give Groupon a parallel sales force and make every human rep sharper the moment they step into a deal. The fuel Foundry runs on is intelligence: which leads are worth pursuing, in what order, and why. That intelligence layer is what this role exists to build and own.

Reporting directly to the CSO, the AI-Powered Growth Intelligence Associate owns Groupon’s lead scoring architecture, routing logic, and pipeline forecasting. You work with one of the most data-rich commercial environments in e-commerce — proprietary consumer transaction signals, merchant health data, and years of conversion history. You don’t configure Salesforce. You extract signal from it, build models on top of it, and use AI to turn raw data into the queue every rep opens each morning. There is no separate analytics team to hand off to. You build it, you own it.

The intelligence layer you build is what Foundry's autonomous agents run on. When an AI agent sequences an outbound lead, reactivates a dormant merchant, or routes an inbound inquiry — it is working from your scoring model. When a rep opens their queue, the ranked order reflects your logic. You sit at the foundation of the AI sales architecture, not at its edge.

North Star

Turn Groupon’s raw lead data into a predictive intelligence system — so every rep opens their queue and finds the right account, in the right order, with the right context, every single day.

 

What You’ll Do:

  • Own the lead scoring model — Design, build, and continuously refine the AI-powered scoring model that determines which leads get prioritised. Use firmographic data, behavioural signals, merchant health indicators, and conversion history to predict outcomes — not just activity.
  • Define and improve lead routing — Translate scoring intelligence into assignment rules that get the right lead to the right rep at the right time. Work with the Sales Operations team on implementation; you define the logic and own the outcome.
  • Build pipeline intelligence — Give the CSO and Sales leadership a live view of where pipeline is healthy, where it is at risk, and what is likely to convert this quarter.
  • Run experiments on live data — Test whether a new signal improves conversion. Measure the delta. Iterate. Every change has a before/after record. You do not ship and move on.
  • Mine Groupon’s data advantage — Use CRM data, call transcripts, and enrichment sources to find signals no competitor can replicate. This is Groupon’s moat. You are building on top of it.

What You Bring:

  • A degree from an Ivy League or equivalent top-tier university strongly preferred — data science, computer science, economics, statistics, or a quantitative field that trained you to think in systems. Up to 2 years of professional experience.
  • Hands-on fluency with Python and data tools — you have built models and connected data sources. You need to build a working pipeline without asking someone else to write the code.
  • Active use of AI tools — you have used LLM APIs (OpenAI, Anthropic, or equivalent) to build something real, and you know the difference between a demo and a deployed workflow.
  • Analytical rigor without a safety net — you build your own measurement frameworks. You do not accept
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