Business optimization project work and coordination of data scientists;
Deployment and maintenance of ML framework/platforms (DVC and MLflow);
Design and optimization of ML architecture and balancing of model computing;
Coordination and maintenance of the ML architecture documentation process;
Health monitoring of ML infrastructure, quality, and performance of ML models;
Development, automation, monitoring, and optimization of ML pipelines.
A degree in Computer Science (technical or economics degree);
3+ years of experience with MLOps (preferably DVC, MLflow, Airflow, Flask, Docker, Git, etc.)
Strong Machine Learning and Data Analysis skills;
Experience with ML frameworks (TensorFlow/Keras, etc.);
Strong Python and SQL;
Experience with ETL and visualization tools;
Good understanding of DWH & Data Lakes architecture;
Good documentation skills;
Intermediate English level or higher.
Previous retail industry experience or in banking/telecommunication companies;
NoSQL experience (HDFS, Hadoop, Spark);
Understanding Kubernetes Architecture for Data Science Workloads.