Personal details
hugo A.
Summary
My mission is to be a catalyst for the growth of the companies I have the opportunity to work with.
Examples of Value-adding initiatives I led in companies I worked for:
# Led the R&D and industrialization of Machine Learning classifiers aimed at predicting the occasion of consumption (i.e., intent) around an order. (Employer: AbInbev)
# Leveraged NLP text processing techniques and transformer models to build text classifiers for key X (forme Twitter) pages, opening the way for the creation of new marketing consulting products(Parrot Analytics)
# Developed Time Series forecasting models to predict the next quarter of sales for dozens of different SKUs, allowing management to fine-tune its sales strategy and adjust the production capacity to minimize the loss of raw materials. (Abbot Laboratories)
Main Skills:
# Tireless problem solver, Lifelong learner
# AWS Certified: Machine Learning Specialty, Data Analytics Specialty, Cloud Developer Associate, and Solutions
Architect Associate.
# AZURE Certified: DP-100 - Designing and Implementing a Data Science Solution on Azure
# GCP Certified: Professional Machine Learning Engineer and Professional Data Engineer
# Main tech-stack:
---- Python, Scikit-learn, Tensorflow, Pytorch, Spark MLLib, SQL, NoSQL, database architecture and management
---- Git and Agile/Scrum methodologies
---- CI/CD: Experience with CircleCI, Kubeflow and Azure DevOps
---- BI tools( Power BI, tableau)
---- Linux and Bash scripting
# Language proficiency levels:
Portuguese(Native), English(Fluent), French(Fluent), Spanish(advanced), German(advanced)
Work Experience
- Perform A/B testing on alpha/beta versions of Large Language Models
- Statistical Data analysis using Python and packages like scikit-learn, statsmodels, xgboost, etc.
Leega is a Data Analytics Consulting Company. As such, I have been assigned to the following clients:
AB-Inbev Belgium (Data Squad):
Worked as Tech Lead, providing technical leadership and guidance to business stakeholders. Also got
my hands dirty performing ETL jobs with SQL and Python. Worked on the orchestration of Jobs using
Airflow dags and Kubernetes (GKE).
(Tech-stack: GCP + data-engineering toolkit)
AB-InBev Global (Consumer Data Intelligence Team):
Working as a Machine learning engineer, performing BigData analysis with Pyspark, orchestration of
jobs with Airflow and Kubernetes. Some of the ML related activities I worked in:
- customer segmentation of our client base (R&D)
Hugo Albuquerque Cosme da Silva - page 1- Code refactoring of ML pipelines related to the enrichment of order attributes(age, gender, city, state)
(MLOps)
- Development of an End-to-End ML pipeline to classify order occasion(Partying, relaxing, etc). (R&D +
MLOps)
(Tech-stack: GCP + Vertex AI)