Tech Lead Machine Learning/Data Engineer

Bachelor’s degree in Statistics, Computer Science, Applied Mathematics, Electrical Engineering, Physics or related areas. Knowledge in probability and statistical modeling. Hands-on experience in statistical analysis and Machine Learning modeling using Python. Hands-on experience on model evaluation, integration, data transformation and deployment. Knowledge in SQL and relational databases. Knowledge with DAG definition and implementation. Experience with Python notebooks, pandas (highly desirable). Experience with PySpark, Airflow (highly desirable). Experience with cloud tools (AWS, Azure, GCP) and orchestration tools (highly desirable). Knowledge about model life cycle, data drift and model drift (highly desirable). Experience with data structures (highly desirable). Experience with finops data treatment and cost saving analysis (highly desirable).

Leverage complex machine learning and statistical models. Implement model to service integration via DAG creations and ETL processes. Evaluate model performance and remodelate accordingly. Build scalable models and DAGs for new workflows. Participate in technical discussions and definitions with a worldwide distributed team. Leverage accurate model architecture and documentation.