Lucas Braga
About Lucas Braga
Lucas Braga is a Senior Data Scientist at Delivery Hero in Berlin, Germany, with extensive experience in data analysis, business intelligence, and machine learning.
Company
Lucas Braga is currently employed by Delivery Hero in Berlin, Germany. He serves as a Senior Data Scientist, continuing a tenure with the company that includes a previous role as a Senior Data Analyst / BI Engineering - Fintech from 2019 to 2020. Delivery Hero is noted for its global footprint in the online food delivery service industry.
Title
Lucas Braga holds the position of Senior Data Scientist. His role involves developing and deploying sophisticated machine learning models and supporting multiple global markets.
Education and Expertise
Lucas Braga obtained a Bachelor's degree from Universidade Federal do Ceará. He furthered his education at The University of Kansas, where he earned a Master's degree in Applied Statistics, Analytics Data Science. His expertise encompasses a range of advanced data science tools and algorithms, including Logistic Regression, Random Forest, XGBOOST, and LightGBM. He is proficient in using platforms such as Airflow, Jenkins, BigQuery, Redshift, and AWS Cloud (EC2, S3, SageMaker, Glue, Athena).
Professional Background
Lucas Braga has a rich and diverse professional background. He began his career at AIESEC, occupying various roles including Local Committee President and National OPS Coordinator in Turkey. He later transitioned to the private sector, working for DHL Global Forwarding in numerous analytical and optimization roles across Germany. Since joining Delivery Hero, he has focused on financial technology and data science.
Notable Achievements
Lucas Braga has made significant contributions to his field. He developed machine learning models for fraud detection and credit risk that led to significant cost savings, estimated between €400K and €800K annually. Additionally, his anomaly detection models provided substantial savings in individual fraud cases. He created over 500 unique features for fraud detection models tailored for markets in Asia and Latin America. His work supports branches across Asia, Latin America, and the Middle East.