Roberto N.

Roberto N.

Machine Learning Engineer

Portugal
Vertrauenswürdiges Mitglied seit 2023
15 Jahre Erfahrung

Roberto specializes in end-to-end ML model deployment, natural language processing (NLP), and deep learning using Python, PyTorch, and Scikit-learn. He is also proficient with cloud platforms, particularly AWS, and has contributed to impactful projects across banking, retail, and entertainment sectors. Notably, he led digital transformation initiatives at Banco do Brasil.

With a passion for robotics and reinforcement learning, Roberto brings innovative thinking and a results-driven approach to every project he undertakes.

Hauptkompetenz

Data Science10 Jahre
Machine LearningMachine Learning4 Jahre
NLP8 Jahre
Data Analytics8 Jahre
46+

Erfahrung5

Majid Al Futtaim

Machine Learning Engineer

Majid Al Futtaim
Retail
Apr 2022 · 4J
  • Developed an end-to-end Programming Optimizer AI tool.
  • ShowtimeAI integrates advanced machine learning with optimization techniques to forecast daily movie session occupancy and devise optimal schedules.
  • By efficiently addressing customer demands for movie sessions, ShowtimeAI has achieved a 13% lift in revenue.
HTMLHTML
FlaskFlask
Data Science
NumPyNumPy
PandasPandas
16+
G42

Data Scientist

G42
Artificial Intelligence (AI)
Mar 2021 - Apr 2022 · 1J 1M
  • Developed Proof of Concept (PoC) models using the Huawei Cloud Platform for customers
Microservices
Data Science
NumPyNumPy
OpenCVOpenCV
PandasPandas
15+
Banco do Brasil

Machine Learning Engineer

Banco do Brasil
Banking and Finance
Jan 2019 - Feb 2021 · 2J 1M
  • Created a set of machine learning templates covering various techniques such as classification, regression, time series, clustering, web scraping, and integer programming. These templates provide an end-to-end solution for machine learning engagements and significantly accelerate the development process by providing a starting point for feature engineering, model optimization, deployment scripts, and more.
  • Developed and deployed a comprehensive DevOps pipeline for machine learning models, significantly reducing deployment time from months to one week. The channel has enabled the deployment of, on average, one model per day.
  • Implemented a service with a Jupyter Lab environment with pre-installed standard libraries and seamless integration with GitLab. The service has seen significant adoption, with 400 users and over 1,000 engagements created in Q1 2021.
  • Mentored new data scientists by sharing best data science, programming, and software engineering practices. This mentorship program is initiated at the start of an engagement and concludes with model deployment. A key deliverable of this mentorship program is the solution architecture design. Areas of focus include Software Architecture, Machine Learning, and DevOps.
Operational Management
Microservices
Prototyping
Data Science
NumPyNumPy
28+
Banco do Brasil

Data Scientist

Banco do Brasil
Banking and Finance
Aug 2015 - Jan 2019 · 3J 5M
  • Developed a Machine Learning Model to predict the digital customers' income. The model was used to create a prioritized list for the call center, resulting in projected savings of US$ 250,000 in the first year.
  • Developed a Machine Learning Model based on a Net Promoter Score survey to discover the main aspects of detractors' experience. The results showed that an imbalance between high waiting and low queue service times was the most significant cause of dissatisfaction. The company changed the queueing policies, which solved the problem country-wide. The model is now used every year to analyze customer happiness.
  • Analyzed the customer segmentation for a new credit card app, using Clustering and Association Rule Analysis to segment and then explain the segments. The results were used to guide the development of the User's Experience (UX) Journey.
Data Science
Scikit-learnScikit-learn
Clustering
Banco do Brasil

Developer

Banco do Brasil
Banking and Finance
May 2007 - Jul 2015 · 8J 2M
  • Developed an automated test framework for mainframe code, which is now part of the DevOps system, continuously testing and checking coverage over 150,000 modules.
  • Created a reservation queue ticket mobile app that allowed premium customers to find the nearest branch and reserve a position on its cashier queue. This app, created in 2015, is still being used nationwide. It was specifically developed the nearest branch search feature using geolocation data.
  • Analyzed performance issues of network equipment for 30 branch offices by evaluating eight variables and using statistical tests. They identified that specific equipment was incompatible with the technology of certain telephone operators, later confirmed by network specialists.
EclipseEclipse
TestNGTestNG
COBOL

Eignungstests

Excellence en ingénierie

Roberto Gesamtleistung in einer 90-minütigen Live-Technikbewertung rangiert im top 5% der überprüften Machine Learning Engineer bei Proxify.

Ausbildung

Universidade de Brasília
Universidade de Brasília
Computer Science2016 - 2018
Universidade de Brasília
Universidade de Brasília
Mathematics2000 - 2005
Universidade de Brasília
Universidade de Brasília
Mathematics2000 - 2005

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