Senior Data Scientist - Performance
Vibe
| Company | Vibe |
| Category | Uncategorised |
| Location | Paris |
| Remote | Hybrid |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 21 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
ABOUT VIBE
At Vibe.co http://Vibe.co, we're reimagining how brands reach audiences in the age of streaming. We believe streaming TV is no longer just a brand awareness play, it's the next great performance marketing channel. We're building the infrastructure to unlock this $100B opportunity.
Vibe.co http://Vibe.co provides an Audience First Streaming TV Advertising solution for marketers to unlock TV as a growth channel. Our all-in-one solution combines hyper-targeted audience segmentation, AI-powered insights and recommendations, real-time campaign optimization, and incrementality measurement, giving brands of all sizes the precision and transparency they've come to expect from social and search, but on TV.
Trusted by over 10,000 brands, Vibe.co http://Vibe.co reaches more than 120 million households across 500+ apps and channels, delivering an average 250% return on ad spend and 20% sales lift. The company hit a $100 million revenue run rate in under two years, ranking among the ten fastest software companies to reach that milestone.
Vibe.co http://Vibe.co's investors include Hedosophia (an early backer of Spotify, Uber, and Airbnb), Elaia, Singular, QuantumLight (Revolut CEO Nik Storonsky's fund), and Illusian (Supercell CEO Ilkka Paananen's fund), as well as angel investors including Carolyn Everson, board member of The Walt Disney Company and Coca-Cola. Nirav Tolia, CEO of Nextdoor, sits on the company's board of directors.
Founded in 2022, Vibe.co http://Vibe.co is widely recognized as the category-defining platform in streaming TV advertising, bringing the power of Meta and Google-style performance marketing to the fastest-growing segment in media.
SENIOR DATA SCIENTIST, PERFORMANCE
ABOUT THE ROLE
You'll join the Performance team — the engineers and scientists who own advertiser outcomes at Vibe, from prediction models to bidding to the delivery stack that drives both. You'll report to the Head of Performance. This role exists because our modeling roadmap has outgrown our current bandwidth, and the scale and diversity of data available to us is about to grow significantly. CTV performance advertising is still being invented: cross-device attribution and identity graphs linking TVs to households look nothing like web display or search, so there's no playbook to copy — you'd be writing it. You'll work with data few others have, joining CTV signal with real-world purchase and behavioral data, which changes how we measure, attribute, and train. Vibe is growing fast enough that the model architecture is still yours to shape, and established enough that your work ships to real advertisers and shows up in the numbers within weeks.
WHAT YOU'LL DO
OWN THE PREDICTION STACK
- Improve our unified multi-task model predicting visits, purchases, and other outcomes simultaneously
- Design shared representations so model heads learn from each other across sparse conversion funnels
- Take ideas from exploration to production: dataset design, architecture, training, and deployment
- Debug production models for gradient issues, convergence failures, drift, and regression
- Partner with Performance engineers building the serving and bidding infrastructure
BUILD THE DATA FOUNDATION
- Design new features from raw signal, including household-level features from our identity graph
- Prepare the modelling stack to absorb new, richer data sources
DRIVE BUSINESS IMPACT
- Optimize models for measurable advertiser uplift, not offline metrics that never ship
- Ship changes to production, measure results, and adjust based on real outcomes
WHAT YOU NEED
- Hands-on deep learning experience shipped in a professional environment
- Strong Python skills, with PyTorch preferred (TensorFlow or JAX also fine)
- Experience diagnosing model failures: data leakage, bias, calibration, distribution shift
- Ability to build algorithms from scratch and reason about what's happening under the hood
- A
You found the opening. Now track it.Tracker, radar and AI drafts in one place.erioun.com →