Senior Data Scientist - Performance

United States Digital Space LLC; Paris (TX); Hybrid; USD 81,000 - 127,000; Full time

Benefits offered by this job

Equity — Employee Stock Ownership Plan

Variable pay

Hybrid flexibility

Health insurance

Meal vouchers

Annual offsite

Tech Syncs

Job summary

the company.co in Paris is seeking a Senior ML Engineer to join the Performance team. You will own the prediction stack, design shared representations, and take ideas from exploration to production that drive advertiser outcomes.

You’ll work with real-world purchase and behavioral data, shipping models that show measurable advertiser uplift, and collaborating with Performance engineers on serving and bidding infrastructure.

Qualifications

• 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, including data leakage, bias, calibration, and distribution shift.

Responsibilities

• Own the Prediction Stack.
• Design shared representations so models learn across sparse conversion funnels.
• Take ideas from exploration to production, covering 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 with features from raw signals and identity graphs.
• Prepare the modeling stack to absorb new, richer data sources.
• Drive business impact by optimizing for measurable advertiser uplift and production deployment.

Skills

Python

PyTorch

Deep learning

Model debugging

Production ML

Data analysis

Tools

Dagster

ONNX

Triton

Job description

About VibeStreaming TV is no longer just a brand awareness channel. It's becoming a core part of the performance marketing mix, alongside search and social. the company.co is building the platform that makes TV work like the rest of the acquisition stack: targeted, measurable, and optimized for results.

the company.co is an Audience First Streaming TV Advertising platform that gives marketers the tools to reach the right audiences, optimize campaigns in real time, and understand what's actually driving business outcomes. With hyper-targeted segmentation, AI-powered recommendations, real-time optimization, and incrementality measurement, the company brings the precision and accountability of digital advertising to the biggest screen in the house.

Today, more than 12,000 brands use the company.co to reach 120 million+ households. And in August 2026, the company.co became a Walmart company, opening up a new chapter for the business and the industry. With Walmart's first-party data and purchase signals now part of the the company platform, advertisers can connect TV advertising to real-world transactions and measure the impact of CTV with a level of precision previously associated with platforms like Google and Meta.

This is a unique moment to join the company. With Walmart's scale, data, and reach behind us, we're building the next generation of TV advertising and creating a more measurable, performance-driven future for the channel.

About the Role

You'll join the Performance team, the group that owns advertiser outcomes at the company end to end, from prediction models to bidding to the delivery stack that puts both into production. You'll report to the Head of Performance. This role exists because the modeling roadmap has outgrown current bandwidth, right as the scale and diversity of data available to the team 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 here, you'd be writing it. You'll work with data few data scientists ever touch, joining CTV signal with real-world purchase and behavioral data in ways that change how the team measures, attributes, and trains. the company 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
• Design shared representations so model heads learn from each other across sparse conversion funnels
• Take ideas from exploration to production, covering 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 the identity graph
• Prepare the modeling stack to absorb new, richer data sources

Drive Business Impact

• Optimize models for measurable advertiser uplift instead of 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, including data leakage, bias, calibration, and distribution shift
• Ability to build algorithms from scratch and reason about what's happening under the hood
• A track record of tying modeling work to a specific business KPI you moved

Nice to Haves

Experience with massive-scale datasets, including billions of impressions, events, or user records

• Deep learning on tabular data and sparse user representations
• Background in CTR/CVR prediction, recommendation systems, or identity graphs and cross-device attribution
• Experience with production ML tooling such as ONNX export, orchestration (Dagster), or inference serving (Triton)

Our Values

At the company, we run on three values: Impact, Ambition, and Urgency. We tie every goal to a real business outcome, think 10x rather than settling for good enough, and move daily rather than waiting for perfect conditions.

You'll thrive here if you own outcomes without needing direction, default to action, and hold yourself to results, not effort.

This is a high-performance environment with high-performance rewards: you'll work alongside people who push you, with real ownership over hard problems in a market that's moving fast.

If that sounds like the best version of your career, we want to meet you.

What We Offer

We will support relocation to Paris for great candidates.

At the company, we want you to build something, own something, and grow fast. Here's how we back that up:

• Equity — Employee Stock Ownership Plan. You're building this; you should own part of it.
• Variable pay — Based on real the company business goals.
• Hybrid flexibility — We're in the Heart of Paris and our team is in 3x a week!
• Health insurance — Full coverage via Alan.
• Meal vouchers — Via Swile.
• Annual offsite — The whole team, once a year, somewhere worth the trip.
• Tech Syncs — Engineering and Product meet in person at least quarterly, worldwide.

Our Interview Process

• Recruiter screen — 30 min. We'll share context; you'll share yours.
• Manager interview — Meet the person you'd work with directly.
• Technical Interview — A real problem, not a trick. We'll work through it together.
• Calibration interview — A senior leader joins to ensure we're holding a consistent, high bar.
• Offer — Fast. We don't let good decisions sit.
• Reference checks — Two calls, handled with discretion.

Equal Opportunity

Vibe is an equal opportunity employer. We evaluate all applicants without regard to race, color, religion, national origin, gender, gender identity or expression, sexual orientation, age, disability, veteran status, or any other characteristic protected by law.

We believe the best ideas come from teams with different backgrounds, perspectives, and experiences. If you need a reasonable accommodation during the application or interview process, please let us know.

Referral Instructions

Being referred? Ask your contact to submit your application directly on your behalf.

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