Work on fraud detection and risk assessment models from data collection to production, collaborating closely with cross-functional teams (engineering, product, finance, operations)
Build, deploy, and maintain machine learning models for:
Ship & Collect: Offline batch inference for recurring payment risk assessment and subscription fulfillment decisions
Voucher Fraud Prevention: Real-time inference at checkout to detect and prevent voucher abuse patterns
Payment Fraud Prevention: Real-time inference at checkout to detect and block fraudulent payment attempts
Monitor model performance, detect anomalies, and communicate insights and recommendations to technical and non-technical stakeholders
Leverage classification, regression, and uplift methodologies to continuously improve fraud prevention and risk assessment solutions
Proactively utilize Generative AI tools to accelerate development cycles, improve code quality, and drive innovative solutions to complex challenges
requirements-expected :
Bachelors, Masters or PhD in statistics, physics, economics, mathematics, computer science, data science or similar
3+ years work experience as a (senior) data scientist, preferably in e-commerce, fintech, or fraud detection
Strong experience with classification and regression models; familiarity with uplift modeling is a plus
Fluency in Python (Numpy, Pandas, Scikit-learn, XGBoost, LightGBM) and experience with Spark/PySpark, Databricks
Experience with AWS services (SageMaker), workflow orchestration (Airflow/Prefect), and feature stores (Tecton is a plus)
In-depth knowledge of handling imbalanced datasets, optimizing precision/recall trade-offs, and evaluating models in production
Experience with real-time model inference, A/B testing, and measuring business impact of ML models
Familiarity with software development practices (Git, Docker, CI/CD pipelines)
Strong communication and collaboration capabilities with technical and non-technical stakeholders
offered :
Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).
