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.
You will design, implement, and optimize machine learning models for clustering, classification, and risk-based segmentation.
You will process and analyze complex transactional datasets, enhancing model performance and scalability.
You will conduct advanced statistical modeling, scenario tuning, and parameterization activities.
You will work extensively with Apache Spark (including internals), Python, and Git to develop, test, and operationalize solutions.
You will collaborate closely with data engineering and business teams to ensure smooth integration and continuous model refinement.
Requirements:
A Master's degree in Data Science or a related discipline is required.
You must have 7+ years of hands-on experience in ML/AI model development following the completion of your master's degree.
A deep understanding of clustering and classification algorithms is necessary.
You should have experience working with structured transactional or behavioral data.
Proficiency with Apache Spark (including internals), Python, and Git is required.
Strong communication skills in English (written and verbal) are essential.
Experience in financial services, banking, or large-scale transactional environments is a plus.
English proficiency should be at a B2+ (Upper-Intermediate or higher) level.
Benefits:
This position is remote, allowing for flexible work arrangements.
It is a full-time role, providing stability and commitment.
You will have the opportunity to work in a dynamic environment with advanced technologies and methodologies.
