(Senior) Data Scientist (m/f/d)

We are looking for a

(Senior) Data Scientist (m/f/d)

(full-time) at our location in Oslo, Berlin, Verl, Stockholm or Amsterdam (flexible working conditions available)

The Data Science (Consumer and Risk) team at Riverty is looking for skilled professionals to build Risk and Fraud machine learning models for our online payment products. Our primary goal is to determine whom to accept and whom to decline based on data from past customers. This involves both detecting fraudulent transactions and identifying trustworthy ones by analyzing payment histories of similar customers.

Your Responsibilities:

• Participate in the entire modeling process, from data cleaning and feature engineering to model training and evaluation.
• Anticipate potential issues in the model-building process and suggest strategies to mitigate pitfalls.
• Engage in coding and code reviews to ensure quality and efficiency.
• Collaborate within a cross-functional team to drive innovation and effectiveness.

What You Bring:

• Experience working with transactional databases or case handling systems.
• A bachelor's, master's, or Ph.D. in a STEM field (e.g. Computer Science, Mathematics, Statistics, Engineering, or related disciplines). 
• Ability to work with imperfect data—data collected for purposes other than machine learning.
• Hands-on experience deploying models into production.
• Proficiency in Python for data science applications.
• Familiarity with common data science frameworks in Python.
• A strong interest in learning new tools and technologies.

Bonus Skills:

• Experience writing production-ready Python code.
• Knowledge of SQL, relational databases, Spark, Databricks, VS Code, and Docker.
• Previous experience in the risk and fraud domain.

Our Hiring Process:

We aim to make our hiring process smooth and transparent:

• Pre-screening Call with HR: A brief conversation to understand your background and motivation.
• Live Coding Challenge: A short technical task to evaluate your coding skills.
• Interview with the Hiring Manager: A discussion about your experience, problem-solving approach, and team fit.
• Bar Raiser Interview with the Department Lead: A final conversation to assess cultural and strategic alignment.

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