Machine Learning Scientist, Personalize Intelligence

This is Adyen

Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.

For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.

Personalize & Adyen Uplift

Adyen is looking for a Machine Learning Scientist to join our team in Chicago focused on Checkout Personalization.

Every checkout is a dynamic decision: which payment methods to display to a shopper, and in what order. While maximizing conversion is a primary objective, it is not the only one. Payment methods carry significantly different transaction costs and fraud exposure, creating a delicate multi-objective trade-off. Steering shoppers toward lower-cost methods risks losing the sale, while optimizing conversion in isolation surrenders margin. The core mission of this role is not picking a side, but mathematically modeling, quantifying, and optimizing this balance.

Operating on hundreds of millions of payments annually gives us an exceptional volume of signal, rapid feedback loops, and a short path from algorithmic iteration to tangible merchant value. Because we only observe shopper behavior on the options displayed, counterfactual reasoning, learning from partial/logged feedback (contextual bandits), and robust offline-to-online evaluation are fundamental daily necessities, not afterthoughts.

About the Role

We are looking for an Applied Machine Learning Scientist / Data Scientist who thrives in deep exploratory research, hypothesis generation, and rigorous empirical analysis. Your primary focus will be on the scientific and algorithmic core: diagnosing current model bottlenecks, formulating novel modeling approaches, designing experiments, and interpreting complex offline and online results.

While our team has dedicated engineering strength to support large-scale distributed pipelines and platform infrastructure, you should possess solid programming fundamentals (Python/SQL) and sound software habits, enabling you to independently write, implement, benchmark, and ship your model code.

The annual base salary range for this role is $177,000 - $230,000 plus RSUs; to learn more about our compensation philosophy, please click here. This position is based out of the Chicago office.

What you'll do

• Identify Improvement Opportunities: Deeply analyze large-scale, complex payment and behavioral datasets to uncover patterns, understand failure modes, and identify untapped leverage points for model improvements.
• Research & Model Architecture: Formulate, develop, and benchmark machine learning algorithms tailored to multi-objective ranking, contextual bandits, and decisioning under uncertainty.
• Rigorous Experimentation & Causal Analysis: Design robust offline validation frameworks, counterfactual evaluation pipelines, and online A/B tests to separate true treatment effects from observational biases.
• Analyze & Interpret Results: Deconstruct experiment outcomes beyond top-line metrics, providing clear quantitative explanations of why models behave the way they do and how trade-offs impact merchant margin and conversion.
• Bring Models to Life: Write clean, modular, and maintainable Python code to implement your models, benchmark them against existing baselines, and collaborate with engineers to guide them through production integration.
• Cross-Functional Partnership: Collaborate closely with product managers and domain specialists to translate ambiguous business objectives into well-posed ML formulations and communicate complex analytical findings to diverse audiences.

Who you are

• Applied Science Mindset: You have 4+ years of professional experience as a Machine Learning Scientist, Data Scientist, or Quantitative Researcher, with a proven track record of developing models that solve real-world decisioning problems.
• Statistical Rigor & Modeling Depth: Strong theoretical grounding in applied statistics, probability, predictive modeling, and experiment design. You think naturally about selection bias, counterfactuals, and multi-objective optimization.
• Analytical Problem Solver: You excel at exploratory data analysis, error analysis, and metric design—you don't just train off-the-shelf models; you diagnose why they fail and where the next 5% gain lies.
• Solid Coding & Implementation

  Skills

  Comfortable writing Python (SQL a plus) to implement your own models end-to-end, using core applied data science libraries (such as pandas, NumPy, scikit-learn, LightGBM/XGBoost, or PyTorch). You can take a model from idea to a working implementation.
• Clear Communicator: Able to articulate the intuition, assumptions, and trade-offs behind your models and translate empirical metrics into actionable business context.

Nice to Have

• Experience with ranking, recommendation systems, or contextual bandits / reinforcement learning.
• Exposure to causal inference and observational data techniques (e.g., uplift modeling, inverse propensity weighting, survival analysis).
• Practical familiarity with containerization (Docker) or experiment tracking tools (e.g., MLflow, Weights & Biases).
• Experience handling tabular or time-series data at scale using tools like Polars, PySpark, or Trino.

Our Diversity, Equity and Inclusion commitments

Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen.

Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!

What’s next?

Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.

Adyen is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

All your information will be kept confidential according to EEO guidelines.