Senior Data Scientist - Performance
HybridParis, Île-de-France, France
Job Summary
Improve the unified multi-task prediction stack for visits, purchases, and outcomes by designing shared representations and taking ideas from exploration to production. Debug production models for gradient issues, convergence failures, drift, and regression while partnering with engineers on the serving and bidding infrastructure. Design new features from raw signal, including household-level attributes from the identity graph, and prepare the modeling stack to absorb richer data sources. Optimize models for measurable advertiser uplift rather than offline metrics, shipping changes to production and adjusting based on real outcomes.
Required Qualifications
- Hands-on deep learning experience shipped in a professional environment
- Strong Python skills
- 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 track record of tying your modeling work to a specific business KPI you moved
Desired Qualifications
- PyTorch
- TensorFlow
- JAX
- Experience with massive-scale datasets — 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: ONNX export, orchestration (Dagster), inference serving (Triton)
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