In this role, you will lead the development of advanced segmentation and classification models, deploying scalable machine learning (ML) solutions across a vast network of business entities.
Responsibilities
Design, implement, and optimize machine learning models for clustering, classification, and risk-based segmentation
Process and analyze complex transactional datasets, enhancing model performance and scalability
Conduct advanced statistical modeling, scenario tuning, and parameterization activities
Work extensively with Apache Spark (including internals), Python, and Git to develop, test, and operationalize solutions
Collaborate closely with data engineering and business teams to ensure smooth integration and continuous model refinement
Requirements
Master's degree in Data Science or a related discipline
7+ years of hands-on experience in ML/AI model development following completion of the master's degree
Deep understanding of clustering and classification algorithms
Experience working with structured transactional or behavioral data
Proficiency with Apache Spark (including internals), Python, and Git
Strong communication skills in English (written and verbal)
Experience in financial services, banking, or large-scale transactional environments is a plus
