Julian Abril
Mathematician & Data Scientist with 5+ years of experience developing solutions for businesses where data is the core of the final product, microservices and REST APIs using Python with a focus on process improvement and automation using Machine Learning, NLP & AI. Experienced leading teams to deliver data products based on client needs. I also have strong experience in reports and indicators for different industries. I consider myself a technology and learning enthusiast - there has never been excuses when learning something new
REVIEWS FROM CLIENTS
Data Engineer, External Workforce at Google:
- Spearheaded the integration of diverse healthtech data sources on Google Cloud, o...
Data Engineer, External Workforce at Google:
- Spearheaded the integration of diverse healthtech data sources on Google Cloud, optimizing data flow. Improved clinical decision support systems for enhanced patient care.
- Engineered advanced data solutions on Google Cloud, boosting system performance. Accelerated medical research and analysis for personalized healthcare approaches.
- Pioneered innovative data solutions, leveraging Google Cloud for improved data quality and accessibility. Facilitated insights to streamline healthcare operations and enhance patient outcomes.
- Develop, Train, Deploy and Continuously Trained NLP models for spam detection. Accelerating 10x the moderation process on millions o...
- Develop, Train, Deploy and Continuously Trained NLP models for spam detection. Accelerating 10x the moderation process on millions of messages on a daily basis.
- Develop automated ETL process to unstructured data for retraining ML models. In order to continuously train, and control the often evolving spam messages problem.
- Implemented Deep Learning computer vision algorithms for granulometry at a big scale applied to coffee trading companies. <li...
- Implemented Deep Learning computer vision algorithms for granulometry at a big scale applied to coffee trading companies.
- Implemented Machine Learning models for detection of humidity, classification, and comparison of quality applied to NIRS technology readings of Coffee.
Tech-Stack: Python, Torch, Keras, Tensorflow, OpenCV, Numpy, GIT, Github, GCP, Jira, Airflow.