Principal Data Scientist2019 - 2020MASH Luxembourg
Technologies: SQL, Databricks, Azure, CatBoost, Python
- Built a fraud prevention model. A type of supervised learning model that was trained to directly optimize a KPI, which resulted in a significant monetary uplift.
- Researched new methods for credit risk modeling, fraud detection, and reject inference.
- Architected the data science infrastructure and workflow.
- Created SLAs with QA, DevOps, and software development teams to streamline the model deployment process.
Senior Data Scientist2018 - 2019collectAI GmbH
Technologies: Amazon Web Services (AWS), XGBoost, Kubernetes, Keras, TensorFlow, Python
- Delivered end-to-end data science projects, including core business ML solutions.
- Researched and implemented state-of-the-art methods for the next generation of AI solution at the company.
- Developed a message classification algorithm that allowed to significantly reduce operational workload for the clients.
- Supported the sales team with ad hoc analyses and/or presentations for clients for customer retention and acquisition.
Data Scientist2016 - 2018Kreditech Holding SSL GmbH
Technologies: Python, Docker, XGBoost, R
- Built credit risk scoring models using gradient boosting.
- Developed a programmatic solution for an optimal bidding strategy in search engine advertisement campaigns.
- Designed and implemented the data processing pipeline for credit risk models.
- Developed a type of monitoring software to identify problems in the conversion funnel using various KPIs, such as conversions, costs, CPA, and so on, that automatically notifies the stakeholders of any abnormalities in the KPIs.