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Summary: This Data Scientist role focuses on outcome optimization in machine learning. The primary objective is to design and enhance models for advertising decisions, ensuring campaigns achieve meaningful results rather than just generating impressions.
Responsibilities:
Responsibilities:
- Build outcome models: Design, train, and evaluate models for various tasks including bidding and forecasting on our advertising platform.
- Run experiments: Design and analyze A/B tests, connecting model performance to real revenue outcomes.
- Engineer features: Create reusable features from raw campaign data and maintain a shared feature store.
- Ship to production: Collaborate with MLOps and Data Engineering to implement models using Vertex AI.
- Collaborate across teams: Work closely with product owners and stakeholders to clearly communicate model impacts.
- 3+ years applying machine learning to real products and delivering impactful models.
- Strong proficiency in Python and SQL, with familiarity in modern ML technologies (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow).
- Solid understanding of statistics and experimentation methodologies.
- Experience with large-scale data and cloud ML tools; knowledge of Google Cloud and Vertex AI is a strong plus.
- Excellent communication skills, capable of explaining complex models to various audiences.
- Experience in adtech, real-time bidding, recommender systems, or marketing science.
- Familiarity with feature stores, MLOps pipelines, or establishing reproducible workflows.
- Team: Data Science / Machine Learning
- Location: Remote
- Type: Full-time
Key Skills
Ranked by relevance
machine learning
cloud
mlops
pytorch
python
sql
ai
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- Posted
- Jul 07, 2026
- Type
- Full-time
- Level
- Not Applicable
- Location
- Poland
- Company
- emagine
Industries
IT Services
IT Consulting
Categories
Engineering
Information Technology
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3 roles aligned with this opportunity
View Job Details
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2026-07-07
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ML Engineer
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