Machine Learning Scientist, Personalize Intelligence
Adyen · Chicago
About this role
## Machine Learning Scientist — Personalize Intelligence (Checkout Personalization) **Company:** Adyen **Location:** Chicago Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft—engineered for ambition. ### About the team / mission Every checkout is a dynamic decision: **which payment methods to display** and **in what order**. While maximizing conversion is a primary objective, it’s not the only one—payment methods differ in **transaction costs** and **fraud exposure**. The role’s core mission is to **mathematically model, quantify, and optimize** this multi-objective balance. Because Adyen processes **hundreds of millions of payments annually**, you’ll work with exceptional signal and rapid feedback loops. Since shopper behavior is only observed for options that were displayed, **counterfactual reasoning**, **contextual bandits**, and **robust offline-to-online evaluation** are essential. --- ## What you’ll do - **Identify Improvement Opportunities:** Analyze large-scale payment and behavioral datasets to uncover patterns, failure modes, and leverage points. - **Research & Model Architecture:** Develop and benchmark ML algorithms for **multi-objective ranking**, **contextual bandits**, and **decisioning under uncertainty**. - **Rigorous Experimentation & Causal Analysis:** Build offline validation and counterfactual evaluation pipelines; run online A/B tests to separate true effects from bias. - **Analyze & Interpret Results:** Go beyond top-line metrics to explain *why* models behave as they do and how trade-offs impact **margin** and **conversion**. - **Bring Models to Life:** Write clean, modular, maintainable **Python** to implement, benchmark, and collaborate on production integration. - **Cross-Functional Partnership:** Work with product managers and domain specialists to translate business goals into ML formulations and communicate results clearly. --- ## Who you are - **Applied Science Mindset:** 4+ years as an ML Scientist / Data Scientist / Quantitative Researcher with a track record of solving real-world decisioning problems. - **Statistical Rigor & Modeling Depth:** Strong grounding in applied statistics, probability, predictive modeling, and experiment design—thinking naturally about selection bias, counterfactuals, and multi-objective optimization. - **Analytical Problem Solver:** Strong EDA/error analysis and metric design; diagnose why models fail and where the next gains come from. - **Solid Coding & Implementation:** Comfortable building end-to-end models in **Python** (SQL a plus) using tools like pandas, NumPy, scikit-learn, LightGBM/XGBoost, or PyTorch. - **Clear Communicator:** Able to explain assumptions, trade-offs, and translate metrics into business context. --- ## Nice to have - Experience with **ranking**, **recommendation systems**, **contextual bandits**, or **reinforcement learning**. - Exposure to **causal inference** and observational data techniques (e.g., uplift modeling, inverse propensity weighting, survival analysis). - Familiarity with **Docker** and/or experiment tracking tools (e.g., MLflow, Weights & Biases). - Experience processing tabular/time-series data at scale (e.g., Polars, PySpark, Trino). --- ## Compensation Annual base salary range: **$177,000 – $230,000** plus **RSUs**. --- ## What’s next Adyen aims to respond within **5 business days**. The interview process typically takes about **4 weeks** (ma
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