Senior ML Engineer - Fraud

[Our mission and customers] Our platform simplifies banking and finance management for SMEs today, so that they can build their tomorrow. We offer a finance management platform with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 53,000+ reviews.Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75. This level of satisfaction is far above typical traditional banking scores, often ranging from 3 to 12, sometimes even lower.[Our journey] Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000 customers across 8 European countries: France, Germany, Italy, Spain, Portugal, Austria, Belgium, and the Netherlands. We have been profitable since 2023, and we are just getting started as we want to become the indisputable European leader in SME finance management.[Our beliefs] We hire for skills and potential. With 80+ nationalities, 45% women, and 56% of women in our leadership team, diversity is simply part of who we are.We've built a discrimination-free hiring process because we believe the best teams are built on merit.[AI at Qonto] We see AI as a catalyst for our success.We always choose thinking over routine. That's why AI is already deeply embedded in how we work - not as a trend, but as a way to raise the bar for the entrepreneurs who count on us. That is why we grant our Qontoers unlimited access to the best AI tools on the market - Claude Code, Cursor, Copilot, Dust, and Notion AI.We want people who experiment without waiting for permission. Who push AI beyond the obvious. Who know when to trust it and, more importantly, when to question it.Already pushing AI limits? You'll fit right in.Are you a talented Machine Learning Engineer ready to make a significant impact? Qonto invites you to join our dynamic Fraud Security team, working alongside experienced ML Engineers to create, deploy, and train powerful machine learning models.⭐ Your mission? Elevate our fraud detection capabilities and ensure the security of Qonto's clients' assets by staying ahead of sophisticated fraudsters.👩‍💻🧑‍💻 As a Machine Learning Engineer at Qonto, you will: Develop and implement risk assessment models, including enhancing our recently launched model for evaluating organizational scam risk. Apply your expertise in Python, SQL, and ML libraries to enhance predictive modeling and feature engineering. Contribute to the entire development cycle, from modeling and development to production deployment, infrastructure management, and incident handling. Collaborate on projects ranging from simple expert rules to advanced machine learning and generative AI applications. Strengthen the team's machine learning capabilities, complementing existing data product skills. Mentor junior team members and contribute to the team's growth and knowledge sharing. Engage in full-stack data engineering to craft robust ETL processes and maintain clean, structured data tables. Take full ownership of the ML infrastructure, utilizing tools like Kubernetes and AWS for efficient model deployment. Continuously improve existing models, balancing the creation of new solutions with the optimization of our current systems🤝 About your future Manager:You will work closely with Jérémy, our Lead Machine Learning EngineerWhat about him: Jérémy leads the risk scoring and anti-fraud team with a pragmatic, results-oriented, and caring management style. He empowers team members to take ownership of their projects while providing support through weekly one-on-one meetings and open communication. Jérémy believes in fostering growth, encouraging skill development, and maintaining a trust-based environment where feedback is valued and micromanagement is avoided.🤔 What you can expect:Team Context: Join an autonomous, cutting-edge team combating financial fraud.Work Environment: Experience a fast-paced, asynchronous, and decisive setting, emphasizing analysis and engineering excellence.Tools in Action: Utilize top-notch infrastructure—Kubernetes, AWS, PostgreSQL, Snowflake, and Kafka—for efficient development.Building Everything: Play a crucial role in shaping a startup-like ecosystem within our scaleup, contributing from the ground up.Ownership: Master the entire process, own the roadmap, and foster openness to innovative ideas.Impactful Role: Make a strong, visible impact, reporting directly to the Leadership team, shaping the future of our mission.With Qonto's rising profile attracting increasingly sophisticated threats, every day brings new challenges to solve.🏅 About YouMindset: You naturally explore the data before building any model, you are proficient in feature engineering techniques to extract meaningful insights from complex datasets.User-focused and outcome-oriented: You want to solve high-impact business problems and deliver value to our users in productionMastery: You are proficient with Python, Pandas, CatBoost, and Scikit-learn. You care about the craft and champion high standards.Outcome-oriented: You value simplicity and think impact first.Software Engineering best practices: you document, version, and test your code systematically.Communication: You appreciate the teamwork that data products typically require, and you have effective communication skills, to build alignment and articulate purpose.Language: You are fluent in English.🌏 Location: You can choose to work in a full-remote mode as long as you're living in (or willing to relocate to) either Germany, France, Italy, Serbia or Spain.At Qonto we understand that true diversity isn't just about ticking boxes on a hiring checklist. Apply regardless of the boxes you tick! Who knows? You may have the missing piece of the puzzle we've been searching for all along.[Our hiring process] Interviews with your Talent Acquisition Manager and future managers (1 hour each) A remote or live exercise to demonstrate your skills and give you a taste of what working at Qonto could be likeOn average, our process lasts 20 working days - more information here on our candidate journey.To know how your personal data will be processed during your application process or to request its deletion, please click here.