<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> Everyone's story matters. Come shape your story with us at Riverty.<br/><br/><strong>But where does that take you?<br/><br/></strong>To one of our 30 hybrid workspaces – designed for exchanging ideas, learning from others, and shaping the way we work. An international community of over 4,000 people, representing almost 80 nationalities across 11 countries. United by one mission: Combining empathy, advanced technology and data-driven insights to keep people and businesses in flow. With payments made for them. So that they don't have to worry about it.<br/><br/><strong>And there's more:</strong> We are part of the family-owned Bertelsmann group. Established. Corporate. In a fast-paced industry. We enable flexible payments in various industries, simplifying the financial management of known brands and helping people repay debt to build financial confidence. In short: shaping FinTech.<br/><br/><strong>We are looking for a<br/><br/></strong><strong>(Senior) Data Scientist (m/f/d) <br/><br/></strong><strong>full-time at our location in Berlin or Amsterdam - </strong><strong>hybrid working conditions available.<br/><br/></strong> <br/><br/>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 who 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.<br/><br/> <br/><br/><strong>What you are expected to do</strong>:<br/><br/><ul><li>Participate in the entire modeling process, from data cleaning and feature engineering to model training and evaluation. </li><li>Anticipate potential issues in the model-building process and suggest strategies to mitigate pitfalls. </li><li>Engage in coding and code reviews to ensure quality and efficiency. </li><li>Collaborate within a cross-functional team to drive innovation and effectiveness.Be involved in the whole modelling process, from data cleaning and feature engineering to model training and evaluation <br/><br/><br/></li></ul><strong>What you bring: <br/><br/></strong><ul><li>A bachelor's, master's, or Ph.D. in a STEM field (e.g. Computer Science, Mathematics, Statistics, Engineering, or related disciplines). </li><li>Experience working with transactional databases or case handling systems. </li><li>Ability to work with unstructured data.</li><li>Knowledge of SQL, relational databases, Spark, Databricks, VS Code, and Docker. </li><li>Hands-on experience deploying models into production. </li><li>Proficiency in Python for data science applications. </li><li>Familiarity with common data science frameworks in Python. </li><li>Experience writing production-ready Python code. </li><li>A strong interest in learning new tools and technologies.</li><li>Previous experience in the risk and fraud domain will be a big plus. <br/><br/><br/></li></ul>Equal Opportunity Employer Statement<br/><br/>We want to be a fair and inclusive employer. We value the diverse perspectives that a diverse workforce brings to the table. Therefore, we are actively looking for people who enrich our company through their identity, background and personal experiences, with or without a disability.<br/><br/><strong>Benefits:<br/><br/></strong><ul><li>At Riverty, you can be who you are. We are committed to creating an inclusive environment and a culture of appreciation, enriched by our employee networks.</li> <li>Prioritize your health with supported sports and leisure activities.</li> <li>Take advantage of our numerous training and development opportunities! Enhance your skills with training offered by the Bertelsmann University, language courses, or leadership training.</li> <li>Benefit from our discounts on Bertelsmann products and financial incentives.</li> <li>With our diverse work models, you can tailor your work to your preferences. Take advantage of mobile office, flexible working hours, and part-time models.</li></ul> </div>