Machine Learning Scientist - Regulatory Reporting Technology

Slashhash; Amsterdam; Hybrid; EUR 85,000 - 120,000; Full time

Job summary

Adyen is seeking a Machine Learning Scientist to join the Regulatory Reporting Tech team in Amsterdam. You will design and scale production-ready ML models for regulatory reporting and risk evaluation, working with Big Data technologies and a product-driven team.

Candidates should have 4+ years of experience in ML or data science, strong Python and Big Data skills, and an engineering-first mindset. The role emphasizes scalable solutions and collaboration across stakeholders.

Qualifications

• 4+ years of experience in ML or data science.
• Strong Python and Big Data skills.
• Engineering-first mindset.
• Experience with Spark/Hadoop ecosystem and production ML.
• Ability to translate complex signals into actionable insights.

Responsibilities

• Design and scale production-ready ML models to support regulatory reporting and risk requirements.
• Own the end-to-end lifecycle from feature engineering within the Big Data ecosystem (Spark/Hadoop) to building internal infrastructure.
• Develop logic that translates complex statistical signals into actionable recommendations for automated root-cause analysis.
• Collaborate with a product-driven team, gathering feedback to ensure technical solutions solve real-world business friction and drive product adoption.

Skills

Python

PySpark

Apache Airflow

Apache Hadoop

Apache Kafka

Machine Learning

Anomaly Detection

Time-Series Analysis

Signal Processing

Causal Inference

Feature Engineering

Big Data

Docker

Kubernetes

SparkStreaming

Tools

Docker

Kubernetes

SparkStreaming

Job description

Adyen is seeking a Machine Learning Scientist to join the Regulatory Reporting Tech team in Amsterdam. The role involves designing and scaling production-ready ML models for regulatory reporting and risk evaluation, working with Big Data technologies, and collaborating with a product-driven team. Candidates should have 4+ years of experience in ML or data science, strong Python and Big Data skills, and an engineering-first mindset.

Technical (Must-have)

• Python
• PySpark
• Apache Airflow
• Apache Hadoop
• Apache Kafka
• Machine Learning
• Anomaly Detection
• Time-Series Analysis
• Signal Processing
• Causal Inference
• Feature Engineering
• Big Data
• Docker
• Kubernetes
• SparkStreaming

Soft Skills

• Communication
• Problem Solving
• Leadership
• Stakeholder Management
• Pragmatism
• Collaboration

Technical (Nice-to-have)

• Apache Flink
• Docker
• Kubernetes

Key Responsibilities

• Design and scale production-ready ML models to support regulatory reporting and risk requirements.
• Own the end-to-end lifecycle from feature engineering within the Big Data ecosystem (Spark/Hadoop) to building internal infrastructure.
• Develop logic that translates complex statistical signals into actionable recommendations for automated root-cause analysis.
• Collaborate with a product-driven team, gathering continuous feedback to ensure technical solutions solve real-world business friction and drive product adoption.

Python, PySpark, Apache Airflow, Apache Hadoop, Apache Kafka, Machine Learning, Anomaly Detection, Time-Series Analysis, Signal Processing, Causal Inference, Feature Engineering, Big Data, Docker, Kubernetes, SparkStreaming, 4 years of relevant experience