Machine Learning Scientist - Regulatory Reporting Technology

Machine Learning Scientist - Regulatory Reporting Technology
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.

MLS - Regulatory Reporting Tech

At Adyen, we are the financial technology platform of choice for the world’s leading companies. The Regulatory Reporting Tech team is critical to ensuring compliance with complex reporting requirements. The Regulatory Financial Modelling & Analytics team, a new workstream within Regulatory Reporting Tech, is responsible for meeting the immediate and increasing need for regulatory financial modeling capabilities and risk evaluation.

We operate at the intersection of data and actionable insights. By leveraging Adyen’s global payment flow data, we apply advanced statistical models to enable accurate reporting and risk evaluation. We are looking for a Machine Learning Scientist to help us further automating and scaling our global regulatory reporting framework to keep Adyen compliant across all markets.

In this role, you will:

Build  – Design and scale production-ready ML models to support regulatory reporting and risk requirements. You will own the end-to-end lifecycle, from feature engineering within our Big Data ecosystem (Spark/Hadoop) to building the internal infrastructure.

Discover  – Move beyond simple detection to build automated root-cause analysis. You will develop logic that translates complex statistical signals into actionable recommendations.

Collaborate  – Work at the heart of a product-driven team. You will sit close to our users, gathering continuous feedback to ensure our technical solutions solve real-world business friction and drive product adoption.

Who You Are:

You have 4+ years of experience as a Machine Learning Engineer or Data Scientist (Anomaly Detection, Time-Series, or Signal Processing).

You have an Engineering-First mindset. You treat ML code like production code and are comfortable managing your own deployments and infrastructure.

You are proficient in Python and Big Data frameworks (PySpark, Airflow, Hadoop, Kafka).

Experience with Spark Streaming/Flink, Docker and Kubernetes is a plus.

You have a strong interest in Causal Inference, you want to prove why something happened, not just that it happened.

You are a pragmatic problem solver. You prioritize business impact and reliability over model complexity, choosing the right tool for the job to ship solutions that work today.

You are proactively taking the lead in projects, from ideation to deployment. You have experience working with a wide range of stakeholders and can clearly communicate complex outcomes to a wide range of audiences.

You can confidently work in a product team with demanding stakeholders, are able to communicate effectively and have the ability to drive the team’s roadmap, alongside the product and engineering leadership of the team.

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…