This role owns data science projects from start to finish: pulling and shaping data in a lakehouse, building machine learning models, and shipping pipelines that stay monitored in production. A strong candidate brings solid marketing analytics grounding, especially measuring campaign performance through return on ad spend, incrementality testing, and marketing mix modeling. Care for data quality, testing, and observability matters as much as modeling skill, along with working smoothly alongside analytics and data engineering teams.

How it fits the AI era

The company builds AI agents for retail, so the work sits close to where automation meets measurement. Models that score campaigns and estimate lift still need careful framing, clean inputs, and human judgment about what the numbers mean. The role keeps a person in charge of design, validation, and deciding when a result is trustworthy enough to act on.

How it builds AI experience

Day to day use of AI coding tools is part of the job,



so comfort with them is expected. The deeper experience comes from working with large retail transaction data and closed loop campaign outcomes, learning how measurement models behave on real commerce signals. Building incrementality tests and mix models on that data gives hands on practice in the kind of applied AI that retail marketing depends on.

Worth showing

- End to end ML delivery
- Databricks lakehouse work
- Marketing mix modeling
- Incrementality testing
- Production pipeline monitoring

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Swiftly

Swiftly provides an AI platform for retailers, wholesalers, and brands that automates workflows, unifies data, and powers personalized marketing, per the company.

📌 Senior Data Scientist (Santa Fe)
🏢 present of AI
📍 Santa Fe