Data Scientist Job Opening at Mollie

Your Opportunity

We are looking for an experienced Data Scientist to join our growing Machine Learning Craft at Mollie. As part of a central team that pioneers ML and GenAI technologies cross-functionally, you will engage directly with predictive modeling to provide decision intelligence across various domains such as Monitoring, Payments, Financial Services, and Customer Experience. Our cloud-based ML Platform supports both the development and deployment of these models, ensuring cutting-edge solutions across the board.

Role Focus

In this dynamic role, your primary focus will be the development of ML models within the Monitoring Domain, addressing critical issues like integrity risk, credit risk, fraud detection, and transaction monitoring. This hands-on position allows you to collaborate closely with other Data Scientists and Machine Learning Engineers, developing solutions in Python and engaging with domain experts and stakeholders to enhance model understanding and feasibility evaluations.

Team Structure

The Monitoring Domain is structured into three teams: Credit & Fraud Monitoring, Customer Monitoring, and Transaction Monitoring. Being part of the Machine Learning Craft, you will link with 10 other top-tier Data Scientists & Machine Learning Engineers across Mollie, precisely focusing on Monitoring challenges.

Location & Work Environment

This role is based out of Mollie’s Amsterdam Hub, with seamless coordination with our teams in Lisbon and Milan through a comfortable, virtual & hybrid collaboration framework.

Key Responsibilities

• Develop and maintain ML models tailored to the Monitoring Domain, ensuring these models are production-ready and deliver significant value to our stakeholders.
• Conduct thorough exploratory data analysis (EDA) and present vital insights to both colleagues & stakeholders.
• Utilize industry-best practices for robust ML model development.
• Work intimately with Machine Learning Engineers to optimize your model and code for our cloud-based ML platform deployment.
• Contribute to bi-weekly DS Community of Practice sessions, which focus on knowledge sharing.
• Assess new potential use cases for ML application within the Monitoring Domain.

What You’ll Bring

• 1-3 years of practical experience in Data Science and Machine Learning, including hands-on model development to production level.
• Proficiency in applied ML with structured data, particularly in solving regression and classification challenges using boosted decision tree algorithms.
• Foundational experience in Generative AI, including LLMs and embedding models, specifically applied in non-chat-based solutions.
• A methodical approach to complex problem-solving and a knack for pragmatic, simple solutions.
• Strong statistical background, excellent software engineering skills, and a passion for coding in Python.
• Effective presentation skills adaptable to a variety of audiences.
• Familiarity with agile methodologies, such as Scrum.

Preferred Qualifications

• Experience with Google Cloud Platform Vertex AI, or similar platforms like SageMaker.
• Background in financial services or fintech, particularly in anomaly detection and large dataset management with tools like (Py)Spark.
• Knowledge of DevOps and MLOps principles.
• Advanced degrees in Machine Learning, natural sciences, or related fields.

Join Mollie's innovative team and lead the way in Machine Learning and Generative AI applications across the financial spectrum. Apply now to become a pivotal part of our growth and success!