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N26, a digital banking platform headquartered in Berlin, is seeking a Technical Product Manager for Applied Machine Learning to join the Intelligent Operations Platforms (IOP) segment. This role sits at the intersection of data science and banking operations, focusing on building and deploying ML solutions that empower internal teams and enable N26 to scale operations efficiently and securely.
You will execute the ML product roadmap by partnering closely with Senior and Lead Product Managers to deliver on the broader machine learning strategy, taking ownership of feature delivery from initial discovery through deployment. You'll act as the day-to-day connector between Data Scientists, ML Engineers, and business stakeholders, translating operational pain points into clear technical specifications, user stories, and acceptance criteria.
Key responsibilities include driving operational and FinCrime automation by delivering predictive models that solve concrete internal bottlenecks, focusing on automating back-office tasks, accelerating document verification, and improving fraud detection accuracy. You will monitor model health and business KPIs by defining, tracking, and analyzing performance metrics for live models, monitoring production accuracy, latency, and false positive rates to identify opportunities for continuous retraining and optimization.
You'll also drive squad backlog execution by partnering with engineering leads to groom product backlogs, write detailed user stories, and participate in daily sprint rituals, ensuring a steady, reliable pace of delivery while upholding strict security standards.
N26 operates across multiple European cities including Vienna and Barcelona, with a 1,500-strong team of more than 80 nationalities. The company offers competitive benefits including a personal development budget, work-from-home budget, fitness and wellness memberships, language apps, public transportation discounts, Premium N26 bank account access, and an additional day of annual leave for each year of service. Relocation support with visa assistance is available.
REQUIREMENTS:
- 4+ years of experience as a Product Manager in a technology-driven environment
- Hands-on experience with, or very strong interest in, data products, analytics, or Machine Learning workflows
- Data Fluency & SQL: Highly comfortable querying and analyzing datasets independently; strong ability to use SQL and data visualization platforms to evaluate model impact and validate hypotheses
- Core ML Fundamentals: Solid understanding of basic machine learning concepts, including classification, regression, decision trees, and the standard model lifecycle from data collection to deployment
- Model Evaluation Understanding: Ability to translate technical model evaluation metrics (precision, recall, F1 score) into practical operational outcomes like saved handling hours or reduced fraud losses
- Technical Communication: Skill in translating complex business rules into precise requirements for engineers, while clearly explaining model outputs and limitations to operational teams
- Execution Bias: Focus on delivering pragmatic, incremental value quickly rather than waiting for perfect data
- Analytical Problem Solver: Curious about complex backend processes, with natural drive to uncover root cause of operational friction
- Banking Quality Standard: Respect for security, compliance, and data privacy requirements necessary when shipping software within a regulated financial institution
