Responsibilities:
Build and deploy end-to-end machine learning solutions from research to production by leveraging advanced algorithms and mathematical techniques to deliver highly predictive models in the fintech space.
Design and run experiments to evaluate new data sources and continuously improve the performance of existing models.
Implement, maintain, and monitor production models using machine learning platform, ensuring scalability, reliability, and long-term performance.
Evaluate model effectiveness both offline and in live environments, with a focus on real-world impact and business relevance.
Act as a technical leader, mentoring teammates, guiding design decisions, and collaborating with global cross-functional partners to drive ML initiatives forward.
MSc/Ph.D. in Statistics, computer science, data science or a related field
5+ years of experience of exploring, building and deploying ML and data systems in production
Strong programming skills in Python focusing on ML frameworks such as Sklearn, XGBoost or TensorFlow
Experience with distributed and stream processing, Cloud ML infrastructure and feature store tools
Expertise in supervised and unsupervised machine learning models (e.g., classification, anomaly detection or clustering)
Experience writing code in Agile, CI/CD-based production environments
Proficient in communicating technical and research ideas and collaborating effectively across teams and organizational stakeholders
Experience in Fintech solutions is a big advantage
