Senior Data Scientist - (Fintech, Antifraud)

Requirements

• Data Science / ML background with expertise in Deep Learning.
• Expert in PyTorch (model design, optimization, deployment).
• Strong coding skills in Python, Git, and ML pipelines.
• Experience with real-time data and production deployment.
• Clear communicator, business-minded, and collaborative.

Nice to Have

• Hands-on with Graph Neural Networks.
• Experience with A/B testing.
• Experience with big data tools such as Spark and BigQuery.
• Background in fraud / risk detection.
• Experience handling imbalanced datasets and designing robust evaluation strategies.

What You'll Be Doing

• Build and deploy ML solutions across both classical ML (LightGBM, scikit-learn) and deep learning (PyTorch, GNNs, Autoencoders) stacks.
• Analyze large-scale transaction data to detect anomalies and trends.
• Own the full ML lifecycle: from data sourcing to deployment, monitoring, explainability, and A/B testing.
• Partner with product, engineering, and ops to scale solutions across 70+ countries.
• Mentor teammates and drive adoption of deep learning best practices.

Perks and Benefits

• Make the most of our hybrid working model and join the team for face-to-face connection and collaboration in our beautiful Berlin campus 2 days a week.
• We offer 27 days holiday with an extra day on 2nd and 3rd year of service.
• Get moving and release those wonderful, mind-boosting endorphins: Health Checkups, Meditation, Yoga, Gym & Bicycle Subsidy.
• Cash. Dough. Cheddar. Whatever you call it, we’ll help you with it: Employee Share Purchase Plan, Sabbatical Bank, Public Transportation Ticket Discount, Life & Accident Insurance, Corporate Pension Plan.
• Look up and go for it. We will support you in developing yourself and your career: 1.000 € Educational Budget, Language Courses, Parental Support.
• The power of getting together over some food is unrivaled. Here are a few ways to help you do that. All the yum: Digital Meal Vouchers, Food Vouchers, Online Canteen, Corporate Discounts.